Breast Angiosarcoma is a rare malignancy, accounting less than 1% of all soft tissue. It comprises primitive and secondary subtypes, such as radiogenic breast angiosarcoma (RAS). Despite the multimodal treatment, angiosarcomas represent an incurable disease for many patients and represent a cause of substantial deterioration of their quality of life. Surgery represents the cornerstone in the management, but high recurrence rates are reported. Electrochemotherapy (ECT) is practicable locoregional treatment in patients with advanced angiosarcoma, in a multimodal therapeutic strategy. ECT palliative benefit includes optimal patient compliance, good local hemostasis control, and local responses. Considering that only 22 cases are described in literature, we reported a rare case of RAS treated with ECT, after a multidisciplinary approach including Next Generation Sequencing (NGS). A literature review about the feasibility of ECT in RAS management was also performed.

Despite the relative scarcity of studies focusing on pharmacotherapy in aphasia, there is evidence in the literature indicating that remediation of language disorders via pharmaceutical agents could be a promising aphasia treatment option. Among the various agents used to treat chronic aphasic deficits, cholinergic drugs have provided interesting results. In the current review, we focused on published reports investigating the impact of acetylcholine on language and further cognitive disturbances. It has been suggested that acetylcholine plays an important role in neuroplasticity and is related to several aspects of cognition, such as memory and attention. Moreover, cholinergic input is diffused to a wide network of cortical areas, which have been associated with language sub-processes. This could be a possible explanation for the positive reported outcomes of cholinergic drugs in aphasia recovery, and specifically in distinct language processes, such as naming and comprehension, as well as overall communication competence. However, evidence with regard to functional alterations in specific brain areas after pharmacotherapy is rather limited. Finally, despite the positive results derived from the relevant studies, cholinergic pharmacotherapy treatment in post-stroke aphasia has not been widely implemented. The present review aims to provide an overview of the existing literature in cholinergic pharmacotherapy interventions in post-stroke aphasia, following an integrated approach by converging evidence from neuroanatomy, neurophysiology, and neuropsychology.

Public key encryption methods are often used to create a digital signature, and where Bob has a public key and a private key. In order to prove his identity, he will encrypt something related to the message with his private key, and which can then be checked with his public key. The main current methods of public-key encryption include RSA and ECC (Elliptic Curve Cryptography), and which involve computationally difficult operations. But these operations have not been proven to be hard in an era of quantum computers. One well-known hard problem is the solving of quadratic equations with $m$ equations with $n$ variables. This is a known NP-hard problem, even in a world of quantum computers. These can be used as post-quantum signature schemes and which involve multivariate equations. In order to understand these methods, this paper outlines a simple example of implementing the oil and vinegar method, and where we have a number of unknown oil variables and a number of known vinegar variables, and where the vinegar variables help convert the hard problem into an easy one.

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.

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.

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.

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).

Natural language Processing (NLP) has significantly transformed in the last decade, especially in the field of Language Modeling. Large Language Models (LLMs) have achieved SOTA performances on Natural Language Understanding (NLU) and Natural Language Generation (NLG) tasks by learning language representation in self-supervised ways. This paper provides a comprehensive survey to capture the progression of advances in Language Models. In this paper, we examine the different aspects of Language Models, which started with a few million parameters but have reached the size of a trillion in a very short time. We also look at how these LLMs transitioned from task-specific to task-independent to task-and-language-independent architectures. This paper extensively discusses different pre-training objectives, benchmarks, and transfer learning methods used in LLMs. It also examines different fine-tuning and In-Context learning techniques used in downstream tasks. It also explores how LLMs can perform well across many domains and datasets if sufficiently trained on a large and diverse dataset. Next, it discusses how, over time, the availability of cheap computational power and large datasets have improved LLM’s capabilities and raised new challenges. As part of our study, we also inspect LLMs from the lens of scalability to see how their performance is affected by the model’s depth, width, and data size. Lastly, we provide an empirical comparison of existing trends and techniques and a comprehensive analysis of where the field of LLM currently stand.

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.

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.

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.

Microwave photonic (MWP) signal processors, which process microwave signals based on photonic technologies, bring advantages intrinsic to photonics such as low loss, large processing bandwidth, and strong immunity to electromagnetic interference. Optical microcombs can offer a large number of wavelength channels and compact device footprints, which make them powerful multi-wavelength sources for MWP signal processors to realize a variety of processing functions. In this paper, we experimentally demonstrate the capability of microcomb-based MWP signal processors to handle diverse input signal waveforms. In addition, we quantify the processing accuracy for different input signal waveforms, including Gaussian, triangle, parabolic, super Gaussian, and nearly square waveforms. Finally, we analyze the factors contributing to the difference in the processing accuracy among the different input waveforms, and our theoretical analysis well elucidates the experimental results. These results provide a guidance for microcomb-based MWP signal processors when processing microwave signals of various waveforms.

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.

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.

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.

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.

This paper focuses on the highly radioactive, long-lasting nuclear waste produced by the currently operating fission reactors and on the way to deal with the sensitive issue of spent fuel reprocessing. The review includes a short description of the fission process and a detailed analysis of the more hazardous radioisotopes produced either by secondary reactions occurring in the nuclear installations or by decay of the fission fragments. Also outlined are the strategies presently adopted to minimize the harmfulness of the nuclear waste to be disposed and discussed advanced options and possible solutions proposed for the recycling of the used fuel and for the reusing of some technologicaly relevant radioisotopes.

Undoubtedly, there is a potential impact of large language models like ChatGPT in revolutionizing information retrieval and knowledge discovery, particularly in the context of the vast amount of electronic material available. On another strong note, the current work offers a first time ever mathematical approach to accurately fine tune perplexity AI, which sets a giant step ahead towards accurate next generations AI. Having started this world leading discovery, the upper and lower bounds of perplexity AI, namely , , respectively, are obtained for the first-time ever. Concluding remarks combined with emerging open problems and next research phase are provided.

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.

Locoregional anaesthetic techniques are invaluable for providing multimodal analgesia for painful surgical procedures. This prospective, randomised study describes a nerve stimulator-guided bra-chial plexus blockade (BPB) in rabbits undergoing orthopaedic surgery in comparison to systemic lidocaine. Premedication was provided with intramuscular (IM) medetomidine, fentanyl and midazolam. Anaesthesia was induced (propofol IV) and maintained with isoflurane. Nine rabbits received a lidocaine BPB (2%; 0.3 ml kg-1), and eight received lidocaine constant rate infusion (CRI) (2 mg kg-1 IV, followed by 100 µg kg-1 minute-1). Rescue analgesia was provided with Fentanyl IV. Carprofen was administered at the end of surgery. Post-operative pain was determined using the Rabbit Grimace Scale (RGS) and a composite pain scale. Buprenorphine was administered accord-ing to pain score for two hours after extubation. Rabbits were filmed during the first two hours to measure distance travelled and behaviours. Food intake and faeces output were compared. Every rabbit in CRI required intraoperative rescue analgesia compared to no rabbits in BPB. How-ever, rabbits in both groups had similar pain scores and there was no difference in administration of postoperative analgesia. There were no significant differences in food intake or faeces produc-tion over 18 hours, and no significant differences in distance travelled, or behaviours examined during the first two hours. BPB seems superior for intraoperative analgesia. Postoperatively both groups were comparable.

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.

Fatigue fractures in materials are the main cause of approximately 80% of all material failures, and it is believed that such failures can be predicted and mathematically calculated in a reliable manner. It is possible to establish prediction modalities in cases of fatigue fracture, according to three fundamental variables in fatigue, such as volume, number of fracture cycles, as well as applied stress, with the integration of Weibull constants (length characteristic). This investigation was carried out mechanical fatigue tests on specimens smaller than 4 mm2 in section of different industrial materials for their subsequent analysis through precision computed tomography in search of microfractures. The measurement of these microfractures, along with their metrics and classifications, was recorded. A convolutional neural network trained with deep learning was used to achieve the detection of microfractures in image processing. The detection of microfractures in images with 480x854 or 960x960 pixels is the primary objective of this network, and its accuracy is above 95%. Images that have microfractures and those that do not are classified by the network. Subsequently, by means of image processing, the microfracture is isolated. Finally, the images that do contain this feature are interpreted by image processing to obtain their area, perimeter, characteristic length, circularity, orientation, and type microfracture metrics. All values will be obtained in pixels and converted to metric units (μm) through a conversion factor based on image resolution.

The spread of fake news poses a serious threat to public trust and informed decision-making. The emergence of AI-generated fake news exacerbates this issue, as it can be produced more rapidly and convincingly than human-generated content. Addressing this issue, our paper introduces a robust approach to detect AI-generated fake news that is applicable across major disinformation domains: Politics and Elections, Health and Medicine, Science and Technology, and Entertainment and Celebrities. Our models differentiate between AI-generated and human-generated news articles while assessing their truthfulness. Utilizing large language models such as ChatGPT, we curated datasets spanning both AI and human generated fake and genuine news. Following extensive data preprocessing and the application of diverse feature extraction techniques, our models were trained using multiple machine learning algorithms. Our results show the feasibility of accurately identifying AI-generated fake news, thereby adding a significant layer of defense in combating misinformation across various sectors. In addition, we have explored the potential utility of transferable machine learning models trained on data from one domain (e.g., politics), when tested on another domain (e.g., health).

The high flammability and lack of charrability of polystyrene (PS) pose significant limitations on its broader applications. Therefore, there is an urgent need for a straightforward and efficient method for the synthesis of flame-retardant PS, which still poses a considerable challenge. In this study, we present an efficient approach to enhance the flame-retardant properties of PS through direct phosphorylating aromatic C(sp2)-H bonds using commercially available and inexpensive manganese catalyst. A range of phosphonates served as reactive substrates to enable a tunable degree of polymer functionalization. The corresponding phosphorylated PS specimens were determined by means of 1H NMR, 31P NMR, FTIR spectroscopy and GPC. Microscale combustion calorimetry (MCC) tests indicate that this protocol indeed enhances the flame-retardant performance of PS. Moreover, other advantages associated with the incorporation of the phosphonate group have been observed, including improved thermal resistance and wettability. This cost-effective strategy of Mn-catalyzed C-H can also be utilized to directly obtain phosphonate modification of waste foamed PS and styrene acrylonitrile copolymer, providing a new method for the purpose of recycling and upgrading PS plastics.

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.

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.

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.

Mercury is a toxic metal, thus, it is an element which has more and more restrictions in its uses, but despite the above, the removal of this metal, from whatever the form in which it is encountered (zero valent metal, inorganic or organic compounds), and from different sources, is of a widespread interest. In the case of Hg(II), or Hg²⁺, the investigations about the treatment of Hg(II)-bearing liquid effluents (real or in most cases synthetic solutions) appear not to end, and from the various separation technologies, adsorption is the most popular among researchers. In this topic, and in the 2019 year, more than 100 publications had been devote to this field: Hg(II)-removal-adsorption. This work examined all of them.

The recently proposed and logically developed paradigm of deep genetical affinity of scientific terms "energy-entropy-information" harmonizes classical and quantum physics with general and special theories of relativity. For the first time in engineering practice, a complex vector-tensor-matrix description of gravitational, thermal and electromagnetic fields in ideal solid, liquid and gaseous media was performed analytically and without preliminary measurements. The basic set of fundamental quantum constants of the standard physical model has been computed with an extreme precision of 1/10^64, which is a natural limit arising due to elementary recursive arithmetic and elementary functional analysis in digital notation.

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.

For the first time in scientific and engineering practice, it is logically and mathematically substantiated, computationally verified and metrologically confirmed that classic and quantum physics, analytical and quantum chemistry, as well as continuous symbolic and discrete digital mathematical analysis, all have computational limits of information entropy, upper 1/10^16 and lower 1/10^64. Mutual displacement of these limits relatively center of Euclidean three-dimensional and of Cartesian two-dimensional space generate sets of quantum dots of mesh topology and weighted average harmonic units of quantum metrics of internal atomic and outer cosmic space, as well as determines limits of communication speed, clock frequency, calculation power and accuracy for any computing machine with subatomic elements of memory. The matrices of functional density and entropy of energy and information fields reconciles classic and quantum physics with continuous and discrete mathematics of special and general relativity.

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.

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.

This article presents a narrative review of neonatal and paediatric complications in post-dated pregnancy and covers scientific views on the aetiology, pathology, risk factors, symptoms and complications of post-dated pregnancy. A pregnancy extending beyond 42 weeks of gestation is termed as a post term pregnancy. There are multiple complications that can occur in the perinatal period, some of the most common ones are stillbirth, asphyxia, meconium aspiration syndrome, fetal distress syndrome, etc which are found to be greater in post-dated pregnancy and hence ultimately leads to increased mortality and morbidity of the new born. Studies have shown that post-term pregnancy also causes increased risk of developing behavioural and emotional problems in children of paediatric age group. It is surprising not much importance has been given to the maternal and neonatal consequences of post- term pregnancies. It is not well understood why some women experience post-dated pregnancies. It is found that factors such as hormones and genetic build up, are responsible for causing post-term pregnancy in an obese female. The treatment and management of a post-term pregnancy still poses a challenge to clinicians in determining the right choice and right time for a particular intervention so that both mother and fetus can be prevented from having complications.

Actively combating post-harvest food spoilage and waste can dramatically increase the efficiency of food utilization worldwide. In climacteric fruits, chemical treatments such as 1-MCP are an effective way of reducing post-harvest spoilage and waste by inhibiting the fruit’s ability to perceive ethylene. 1-MCP treatment is increasingly being used to explore the complex nature of ripening physiology at a fundamental level, however, differences in application and quantitation methods create difficulties in comparing conclusions across studies. Here we report an effective and reproducible method for 1-MCP application and quantitation for small-medium sized research applications. By use of surrogate alkene standards 1-butene and cis-2-butene, the highly volatile and elusive 1-MCP molecule can be identified and quantified by gas chromatography and subsequent standard curves may be developed. It is hoped that the methodology outlined here can help standardize consistent 1-MCP application for post-harvest research without excessive investment in specialized equipment.

Background: Optimal hypofractionated schedule of post-prostatectomy radiotherapy remains to be established. We evaluated treatment outcomes and toxicity of the moderately hypofractionated post-prostatectomy radiotherapy in 16 daily fractions delivered with IMRT/VMAT. The treatment schedule selection was motivated by limited technology resources. Methods: One hundred consecutive M0 patients with post-prostatectomy radiotherapy were evaluated. Radiotherapy indication was adjuvant (ART) in 19%, early salvage (eSRT) in 46% and salvage (SRT) in 35%. The dose prescription for prostate bed PTV was 52.8 Gy in 16 fractions of 3.3 Gy. The Common Terminology Criteria v.4 for Adverse Events scale was used for toxicity grading. Results: The median follow-up was 61 months. Five-year biochemical recurrence-free survival (bRFS) was 78.6%, distant metastases-free survival was 95.7% and overall survival was 98.8%. Treatment indication was the only significant factor for 5-year bRFS in multivariate analysis which was 84.6% vs. 67.6% for ART or eSRT vs. SRT respectively (HR 0.15, 95% CI 0.05–0.47, p=0.001). Acute GI toxicity grade 2 was recorded in 24%, grade 3 in 2% and acute GU toxicity grade 2 in 10% and no grade 3. Cumulative rate of late GI toxicity grade ≥2 was observed in 9% and late GU toxicity grade ≥2 in 16%. Conclusion: Observed results confirmed efficacy and acceptable toxicity of post-prostatectomy hypofractionated radiotherapy in 16 daily fractions.

Smoking during pregnancy remains one of the most significant risk factors for poor birth outcomes. The Loma Linda University Health Comprehensive Tobacco Treatment Program (CTTP) is the largest maternal tobacco cessation program in San Bernardino County – the largest county in the contiguous US. CTTP is an eight week, incentivized, behavioral intervention for tobacco cessation for pregnant smokers. As part of program evaluation, we used a retrospective cohort design to assess smoking abstinence and to identify predictors of relapse/smoking after enrollment. Among CTTP cohort enrollees (n=233) from 2012-2013 we found: 1) a 28.4% 8 week point prevalence abstinence (PPA), and at a median of 9 months of follow-up after the PPA, 81.6% continued to indicate tobacco cessation, and 2) a high rate of relapse or loss to follow-up (56%). Our modeling of relapse/smoking after enrollment indicated that this was higher in young mothers, non-Hispanic mothers (White, Black), first/third trimester mothers, and rural mothers. The evaluation identified efficacy of the behavioral model at 8 weeks, but that relapse/smoking was occurring in disparity populations. Formative research is needed to expand the programmatic outreach and enrollment of mothers wanting to quit smoking.

Postpartum depression (PPD), a condition that affects up to the 15% of mothers in high-income countries, reduces attention toward the needs of the child and it is among the first causes of infanticide. PPD is usually identified using self-report measures and therefore the diagnosis may not always be valid. Previous studies highlighted the presence of significant differences in the acoustical properties of the vocalizations of children of depressed and healthy mothers. In this study, cry episodes of infants of depressed and non-depressed mothers are analyzed to investigate the possibility that a machine learning model can identify PPD in mothers from the acoustical properties of infants' vocalizations. Acoustic features (F0, F1-4, Intensity) are first extracted from recordings of crying infants, then novel cloud-based artificial intelligence models are employed to identify maternal depression versus non depression from estimated features. Trained model shows that commonly adopted acoustical features can be successfully used to individuate Post-Partum Depressed mothers with very high accuracy (89.5%).

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.

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.

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.

Introduction: Despite more than one year passed since the first cases of SARS-CoV-2 were reported, there is still no consensus on the definition and clinical management of post-acute-COVID-19. The condition has heterogeneously been named as Chronic COVID syndrome, Post COVID-19 Syndrome, post-acute sequela of SARS-CoV-2 (PASC), and the more familiar long COVID. Method: In order to capture all relevant published studies, we undertook a multi-step search with no language restriction. The following four-step search strategy was utilized: First, a preliminary (limited) search was conducted on January 20, 2021, in Google Scholar and PubMed to identify the appropriate keywords. Then, on January 30, 2021, we adopted a search strategy of electronic databases from Cochrane Library, PsycINFO, PubMed, Embase, Scopus, and Web of sciences, using those keywords. Then, after duplicate removal, we screened all titles, abstracts, and full texts. This resulted in 66 eligible studies. Subsequently, after a forward and backward search of their references and citations an additional 54 publications were found, resulting in a total of 120 publications that formed the basis of the present analysis. The titles, abstracts, and full-texts of non-English articles were translated using Google Translate for further evaluation. We conducted our scoping review based on the PRISMA-ScR Checklist.Results: We found only one randomized clinical trial in our search. Of the 67 original studies, 22 were cohort and 28 were cross-sectional studies totaling 74.6% of the original studies. Of the total of 120 publications, 59 (49.1%) focused on signs and symptoms, 28 (23.3%) were focused on management, and 13 (10.8%) focused on pathophysiology. Ten (9%) publications focused on imaging studies. Ninety-one percent of the original investigations came from high and upper-middle-income countries, highlighting the scarcity of reports originating from low-income and lower-middle-income countries.Conclusion: The predominant symptoms among those with the so-called “Long COVID” were: fatigue, breathlessness, arthralgia, sleep difficulties, and chest pain. Recent reports also point to the risk of long-term sequela with cutaneous, respiratory, cardiovascular, musculoskeletal, mental health, neurologic, and renal involvement in those who survive the acute phase of the illness. The ambiguity and controversies in its definition have impaired proper recognition and management of those requiring additional support following the resolution of the acute phase of this infection. This has resulted in long-standing distress for the patients and their families. Our findings highlight the need for a multidisciplinary approach, support, and rehabilitation for these patients in terms of long-term mental and physical health.

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.

Amid increasing deforestation, surface fires reaching the forest understory are one of the primary threats to Amazonian ecosystems. Despite extensive research on post-fire mortality in woody species, literature on palm resilience to fire is scant. This study investigates post-fire mortality in four understory palms—Bactris maraja Mart., Chamaedorea pauciflora Mart., Geonoma deversa (Poit.) Kunth, Hyospathe elegans Mart., and juvenile individuals of Euterpe precatoria Mart. Objectives included: a) comparing post-fire responses; b) developing mortality models based on severity variables; and c) evaluating if diameter protects bud stems from heat flux. Conducted at the edge of an Ombrophylous Forest in Alto Juruá Acre, Brazil (7°45'S, 72°22'W), the experiment subjected 85 individuals to controlled burning in a 1 m² area near the stipe, with temperature sampling using K thermocouples. Results showed varying mortality rates among species, with larger stipe diameter correlating to reduced mortality. Canopy burning patterns significantly influenced mortality, especially for Euterpe precatoria. Species exhibited diverse regrowth capacities, with B. maraja showing the highest number and tallest basal resprouts. This study underscores post-fire plant mortality as a critical indicator of fire severity, essential for understanding its ecological impacts.

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.

COVID-19, the fear it engendered, and the policy measures to manage its spread have disproportionately impacted the wellbeing of children and adolescents (CAs). We present an intensive critical realist case study of the impact of COVID-19 on the health and wellbeing of CAs in Rwanda, seeing it as much a social and political crisis as a medical and public health one. To do this, we carried out interviews with a purposive sample of 25 leaders with a working knowledge of children and young people; they were more likely than the CAs themselves to observe changes across the CA population within their remit and more likely to be looking for general explanations rather than individual experiences. The findings show that CAs' responses to the changes wrought on their lives by Covid-19 were conditioned by their age, gender, social class and if they lived in urban or rural areas. However, Covid19 has not just revealed the structural weakness of the Rwandan health system but of education, social protection, child protection, employment, family, and financial systems. The pathway to (adverse) impacts of COVID-19 on CAs is conditioned by these institutions and their interactions together with structural socioeconomic inequalities both within Rwanda and globally.

In recent decades, microwave photonic channelization has developed rapidly. Characterized by low loss, high versatility, large instantaneous bandwidth, and immunity to electromagnetic interference, microwave photonic channelization techniques coincides with the requirements of modern radar and electronic warfare for receivers. The advanced microresonator-based optical frequency combs are promising platforms for the research of the photonic channelized receivers, which take full advantage of multicarrier and large bandwidth, and accelerate the integration process of microwave photonic channelized receivers. In this paper, we review the research progress and trends in microwave photonic channelization, focusing on schemes that utilize integrated microcombs. Finally, we discuss the potentials of microcomb-based RF channelization, as well as the challenges and limitations, and provide routes and perspectives for future developments in the context of on-chip silicon-based photonics.

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.

Our aim was to evaluate the immune response of healthcare workers included in the RIPOVAC study, after receiving a booster dose (third dose), in terms of intensity and persistence of induced antibodies. In the second phase of RIPOVAC study, between December 2021 and January 2022, eight months after the second dose, 389 voluntary, immunocompetent, non-pregnant healthcare workers received a booster dose of SARS-CoV-2 vaccine, and a serum sample was obtained. Two groups of patients were established: with and without previous SARS-CoV-2 infection. In order to quantify anti-S1 IgG (AU/mL) we used CMIA (Abbott). All the health workers were anti-S IgG positive 8 months after receiving the booster dose of the vaccine, with a mean of 17040 AU/mL. In 53 patients without previous infection, antibody levels had increased by a mean of 10762 AU/mL. This figure is 7 times higher than the one produced after the second dose (1506 AU/mL). The booster dose produces a robust elevation of the antibody level, which persists at 8 months with levels up to values significantly higher than those reached after the second dose, that allow to predict a persistence of more than one year. The study demonstrates the efficacy of the booster dose of anti-SARS-CoV-2 vaccines.

Microwave photonic (MWP) transversal signal processors offer a compelling solution for realizing versatile high-speed information processing by combining the advantages of reconfigurable electrical digital signal processing and high-bandwidth photonic processing. With the capability of generating a number of discrete wavelengths from micro-scale resonators, optical microcombs are powerful multi-wavelength sources for implementing MWP transversal signal processors with significantly reduced size, power consumption, and complexity. By using microcomb-based MWP transversal signal processors, a diverse range of signal processing functions have been demonstrated recently. In this paper, we provide a detailed analysis for the processing inaccuracy that are induced by the imperfect response of experimental components. First, we investigate the errors arising from different sources including imperfections in the microcombs, the chirp of electro-optic modulators, chromatic dispersion of the dispersive module, shaping errors of the optical spectral shapers, and noise of the photodetector. Next, we provide a global picture quantifying the impact of different error sources on the overall system performance. Finally, we introduce feedback control to compensate the errors caused by experimental imperfections and achieve significantly improved accuracy. These results provide a guide for optimizing the accuracy of microcomb-based MWP transversal signal processors.

In the past decades, a significant rise in the adoption of streaming applications has changed the decision-making process for the industry and academia sectors. This movement led to the emergence of a plurality of Big Data technologies such as Apache Storm, Spark, Heron, Samza, Flink, and other systems to provide in-memory processing for real-time Big Data analysis at high throughput. Spark Streaming represents one of the most popular open-source implementations which handles an ever-increasing data ingestion and processing by using the Unified Memory Manager to manage memory occupancy between storage and processing regions dynamically, which is the focus of this study. The problem behind memory management for data-intensive stream processing pipelines is that the incoming data is faster than the downstream operators can consume. Consequently, the backpressure of Spark acts in the opposite direction of downstream operators. In such a case, the incoming data overwhelms the memory manager and provokes memory leak issues. As a result, it affects the performance of applications generating, e.g., high latency, low throughput, or even data loss. In such a case, the initial intuition motivating our work is that memory management became the critical factor in keeping processing at scale and system stability of Spark. This work provides a deep dive into Spark backpressure, evaluates its structure, presents the main characteristics to support data-intensive streaming pipelines, and investigates the current in-memory-based performance issues.

Recent years have seen the growing adoption of non-relational data models for representing diverse, incomplete data. Among these, the RDF graph-based data model has seen ever-broadening adoption, particularly on the Web. This adoption has prompted the standardization of the SPARQL query language for RDF, as well as the development of a variety of local and distributed engines for processing queries over RDF graphs. These engines implement a diverse range of specialized techniques for storage, indexing, and query processing. A number of benchmarks, based on both synthetic and real-world data, have also emerged to allow for contrasting the performance of different query engines, often at large scale. This survey paper draws together these developments, providing a comprehensive review of the techniques, engines and benchmarks for querying RDF knowledge graphs.

The Open Access (OA) publishing model that is based on article processing charges (APC) is often associated with the potential for more transparency regarding the expenditures for publications. However, the extent to which transparency can be achieved depends not least on the completeness of data in APC monitoring systems. This article investigates two blind spots of the largest collection of APC payment information, OpenAPC. It aims to identify likely APC-liable publications for German universities that contribute to this system and for those that do not provide data to it. The calculation combines data from Web of Science, the ISSN-Gold-OA-list and OpenAPC. The results show that for the group of universities contributing to the monitoring system, more than half of the APC payments are not covered by it and the average payments for non-covered APCs is higher than for APCs covered by the system. In addition, the group of universities that does not contribute to OpenAPC accounts for two thirds of the number of APC-liable publications recorded for contributing universities. Regarding the size of these blind spots, the value of the monitoring system is limited at present.

With the widespread use of mobile phones, increasing use of mobile applications in different areas of life have gained a large place. Between the reasons of the preference of the rapid increasing number of apps in the application markets of the different platforms, the aesthetic appereance of the icons that apps have perhaps the most important one. In this study, the visual symmetrical side of the icons of the most downloaded apss which are developed for preparing to Public Servant Exam in Turkey is emphasized. Two different types of data are obtained with working on the icons with image processing technique by using Mathworks Matlab program and survey method which is applied on Korkut Ata University students. By comparing the obtained data with the binary logistic regression method, it was determined that the visual symmetry in the apps’ icons partially contributed to the aesthetic appreciation.

Integrated Kerr micro-combs, a powerful source of many wavelengths for photonic RF and microwave signal processing, are particularly useful for transversal filter systems. They have many advantages including a compact footprint, high versatility, large numbers of wavelengths, and wide bandwidths. We review recent progress on photonic RF and microwave high bandwidth temporal signal processing based on Kerr micro-combs with spacings from 49-200GHz. We cover integral and fractional Hilbert transforms, differentiators as well as integrators. The potential of optical micro-combs for RF photonic applications in functionality and ability to realize integrated solutions is also discussed.

Over the past 30 years, the use of field spectroscopy has risen in importance in remote sensing studies for the characterization of the surface reflectance of materials in situ within a broad range of applications. Potential uses range from measurements of individual targets of interest (e.g. vegetation, soils, validation targets etc.), to characterizing the contributions of different materials within larger spatially-mixed areas as would be representative of the spatial resolution captured by a sensor pixel (UAV to satellite scale). As such, it is essential that a complete and rigorous assessment of both the data-acquisition procedures, and the suitability of the derived data product be carried out. The measured energy from solar-reflected range spectroradiometers is influenced by the viewing and illumination geometries and the illumination conditions which vary due to changes in solar position and atmospheric conditions. By applying corrections, the estimated absolute reflectance (Rabs) of targets can be calculated. This property is independent of illumination intensity or conditions and is the metric commonly suggested to be used to compare spectra even when data are collected by different sensors or acquired under different conditions. By standardizing the process of estimated Rabs, as is provided in the described toolkit, consistency and repeatability in processing are ensured and the otherwise labor intensive and error-prone processing steps are streamlined. The resultant end data product (Rabs) represents our best current effort to generate consistent and comparable ground spectra which have been corrected for viewing and illumination geometries as well as other factors such as the individual characteristics of the reference panel used during acquisition.

The sentiment of a word varies based on its context of usage: the words used around it and the part-of-speech it is used as. This paper proposes a technique to suggest the sentiment of a word by combining its part-of-speech and the semantic similarities of its co-occurrences with both context-specific and pre-trained embeddings to achieve powerful and fast results. A study was conducted across domains and sub-domains to measure variance of sentiment by switching domains and switching context within the same domain. Re-scoring a commonly used polarity lexicon showed that 10% of words changed scores while switching domains and 8% changed scores within domains while switching context. Part of Speech analysis on 65,353 commonly used sentiment lexicons showed that 81% of sentiment bearing (non-neutral) lexicons were of the tags NN (Common Noun), JJ (Adjective) or NNS (Proper Noun).

This study aimed to investigate the effect of adding Mirror Visual Feedback Therapy (MFT) after Dry Needling (DDN) on sensitivity and motor performance in patients diagnosed with Post-Needling pain from Myofascial Trigger Points (MTrPs) in lateral elbow pain patients. A randomized, controlled, two-arm pilot trial following Consolidated Standards of Reporting Trials (CONSORT) was conducted at the European University of Madrid between February 1, 2023, and June 2, 2023. A total of 49 patients (F=23, M=26) were randomly assigned to the Experimental Group Deep Dry Needling, Ischemic Compression, Cold Spray, Stretching, and Mirror Therapy (n=25), and the others receiving the same interventions without Mirror Therapy (n=24). Pre- and post-treatment assessments encompassed Post-needling pain (VAS), pressure pain threshold (PPT), two-point discrimination threshold (TPDT), and maximum hand grip strength (MHGS). Post-needling pain intensity in the EG showed statistically significant reductions (MD = 0.400, SEM = 0.271, W = 137.00, p = 0.047) following the addition of MT to the DDN protocol. Similarly, PPT exhibited significant improvements (MD = 0.148 Kg/cm2, SEM = 0.271, W = 262.00, p < 0.001). However, TPDT and MHGS did not show significant differences between initial and post-treatment measurements. The addition of MFT to DDN for MTrPS in lateral elbow pain reduced Post-needling pain and influenced on sensory perception in lateral elbow pain patients with Myofascial Trigger Points. Despite observed clinical effects not reaching statistical significance, these findings offer valuable insights for future research considerations.

Microwave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When implemented using microwave photonic (MWP) technologies, also known as MWP transversal filters, they provide competitive advantages over their electrical counterparts, such as low loss, large operation bandwidth, and strong immunity to electromagnetic interference. Recent advances in high-performance optical microcombs provide compact and powerful multi-wavelength sources for MWP transversal filters that require a larger number of wavelength channels to achieve high performance, allowing for the demonstration of a diverse range of filter functions with improved performance and new features. Here, we present a comprehensive performance analysis for microcomb-based MWP spectral filters based on the transversal filter approach. First, we investigate the theoretical limitations in the filter spectral response induced by finite tap numbers. Next, we analyze the distortions in the filter spectral response resulting from experimental error sources. Finally, we assess the influence of input signal’s bandwidth on the filtering errors. These results provide a valuable guide for the design and optimization of microcomb-based MWP transversal filters for a variety of applications.

With the development of satellite load technology and very-large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. Limited by severe size, weight, and power consumption constraints, a key challenge of on-board SAR imaging system design is to achieve high real-time processing performance. In addition, with the rise of multi-mode SAR applications, the reconfiguration of the on-board processing system is beginning to receive widespread attention. This paper presents a multi-mode SAR imaging chip with SoC architecture based on the reconfigurable double-operation engines and multilayer switching network. We decompose the commonly used extend chirp scaling (CS) SAR imaging algorithm into 8 types of double-operation engines according to the computing orders, and design a three-level switching network to connect these engines for data transition. The CPU is responsible for engine scheduling based on data flow driven with instructions to implement each part of the CS algorithm. Thus, multi-mode floating-point SAR imaging processing can be integrated into a single Application-Specific Integrated Circuit (ASIC) chip instead of relying on distributed technologies. As a proof of concept, a prototype measurement system with chip-included board is implemented, and the performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. A chip requires 9.2 s, 50.6 s and 7.4 s for a stripmap with 16,384×16,384 granularity, multi-channel stripmap with 65.536×8192 granularity and multi-channel scan mode with 32,768×4096 granularity and 6.9 W for the system hardware to process the SAR raw data.

Grain legumes are fair sources of protein, amino acids and energy, and can be used as a replacement for soybean meal in poultry feed formulations as the soybean meal becomes short in supply and costly. However, a concern associated with the use of grain legumes in poultry feeding is the presence of antinutritional factors. Effective processing and utilisation of these grain legumes in poultry feeding are well documented. The current review focuses on four selected grain legumes (lupins [Lupinus albus and Lupinus angustifolius], field peas [Phaseolus vulgaris], faba beans [Vicia faba] and chickpeas [Cicer arietinum]) and their nutrient content, the presence of antinutritional factors, processing methods and feeding value, including updated data based on recent research findings.

Considering nutritional qualities of gofio (Gf) and aloe vera juice (AVJ), their combination is indicated as an easy and fast source of ingest of basic bio elements. As the texture of the final product must be accepted by customers, the influence of Gf concentration on the rheological behavior of Gf/AVJ suspensions was determined. Shear thinning index of AVJ maintains unaltered despite the presence of Gf particles, although the viscosity value increases as expected. Linear viscoelastic studies on Gf/AVJ confirmed this is a viscoelastic liquid that changes from chewy to creamy texture with Gf concentration increase.

Retweet prediction is an important task related to different problems such as information spreading analysis, the automatic detection of fake news, social media monitoring, etc. In this study we explore the possibilities of retweet prediction based on heterogeneous data sources. In order to classify the tweet according to the amount of retweets, we combine features extracted from the multilayer network and the text. More specifically, we introduce a multilayer framework that proposes the multilayer network representation of Twitter. This formalism captures different users' actions and complex relationships as well as other key properties of communication on Twitter. We select a set of local network measures from each layer and construct a set of multilayer network features. In addition, we adopt a BERT-based language model, namely Cro-CoV-cseBERT to capture high-level semantics and structure of tweets as a set of text features. Then, we train six machine learning (ML) algorithms: random forest, multilayer perceptron, light gradient boosting machine, category embedding model, neural oblivious decision ensembles and attentive interpretable tabular learning model in the task of retweet prediction. We compare the performance of all six algorithms in three different setups (i) using only text features, (ii) using only multilayer network features and (iii) using both sets of features. We evaluate all setups in terms of standard evaluation measures i.e. precision, recall, F1-score and accuracy. For this task, we first prepare and use an empirical dataset of 199,431 tweets in the Croatian language posted during the period between January 1, 2020 and May 31, 2021. Our results indicate that by integrating multilayer network features with text features the prediction model would perform better than using just one set of features.

Abstract. Indonesia has developed several superior soybean varieties. Each soybean variety has different physical and chemical properties that can affect processed products and soybean quality. The purpose of this study was to determine the physical, chemical, and functional properties of three superior early-maturing soybean varieties. The research was conducted in Maros, Indonesia in 2022 by planting the Dega-1, Grobogan, and Gepak Kuning varieties and repeated them 6 times. The yields of the three soybean varieties Dega-1, Grobogan, and Gepak Kuning were taken at 1 kg each and 3 repeated, then further analysis of chemical compounds is carried out in the laboratory. The results showed that for physical characteristics, the largest seed size was in Dega-1 (18.57 g per 100 seeds) and the smallest in Gepak Kuning (8.29 g). The highest bulk density of soybean seeds was in the Grobogan and Dega-1 varieties (0.79 kg per m3) and the lowest was in Gepak Kuning (0.77 kg per m3 ), and the lowest number of damaged seeds was in Dega-1 (6.67%) and the highest in Grobogan (11.33). %). Chemical characteristics, highest protein content in Gepak Kuning (39.72%) and lowest in Dega-1 (36.62%), lowest fat content in Dega-1 (12.63%) and highest in Gepak Kuning (14.49%), highest phosphorus content in Gepak Kuning (0.59%) and the lowest was in Grobogan (0.53%), the highest calcium content was in Gepak Kuning (0.40%), and the highest FFA value was in Dega-1 (0.93) and the lowest in Gepak Kuning (0.81). Based on physical properties, Dega-1 is the best compared to the other two soybeans. Meanwhile, based on the size of starch granules, Gepak Kuning gave the best results. For chemical characteristics, in general, GepakKuning has the best quality compared to Grobogan and Dega-1. It can be concluded that Gepak Kuning has the most potential to be developed in supporting food and non-food products, especially in Indonesia.

Background. There are few studies about post myocardial infarction follow-up using telemedicine. We organized a post-discharge telemedicine service with a dedicated team. To do this, it was necessary that all stakeholders involved in the organization and use of the telemedicine service were properly educated and informed. Methods. We designed a theoretical-practical mini-course, to train healthcare personnel and increase skills, with excellent learning outcomes and satisfaction. Thereafter, we enrolled patients affected by acute myocardial infarction with ST elevation (STEMI), MINOCA (myocardial infarction with no obstructive coronary atherosclerosis), Takotsubo syndrome or spontaneous coronary dissection, and high-risk acute myocardial infarction without ST elevation (NSTEMI). At discharge, the cardiology technician performed counselling for the patient; using regional platforms, televisit at 1 and 4 months monitored major adverse cardiac events (MACE), heart failure, arrhythmias, unstable angina and non-cardiovascular events, therapy adherence, target therapy and customer satisfaction. Results. Between November 2021 and February 2023, we enrolled 110 patients: 72% affected by STEMI, 22% by NSTEMI. At the 1-month follow up, 12 patients did not reach pressure target and 23 patients did not reach LDL target. We observed three in hospital readmission, three in hospital visits for further investigation and one death. To date, a four months follow up was performed for 54 patients. No readmissions or deaths occurred. We detect a rate of 96% of customer satisfaction. Conclusion. A health coordination center with a dedicated team makes televisit safe as a follow-up for post myocardial infarction patients. Before, it is fundamental for healthcare professionals the acquisition of theoretical knowledge and updates and the acquisition of manual, technical and practical skills.

Leishmania infantum is causative of visceral leishmaniasis (kala-azar), the most severe form of leishmaniasis, lethal if untreated. Few years ago, re-sequencing and de novo assembling of the L. infantum (strain JPCM5) genome was accomplished, and now we aimed to describe and characterize the experimental proteome of this species. In this work, we have performed a proteomic analysis from axenic cultured promastigotes and carried out a detailed comparison with other Leishmania experimental proteomes published to date. We identified 2,352 proteins based on the search of mass spectrometry data against a database built from the six-frame translated genome sequence of L. infantum. We have detected many proteins belonging to organelles such as glycosomes, mitochondria or flagellum, as well as many metabolic enzymes, and a large number of putative RNA binding proteins and molecular chaperones. Moreover, we listed the proteins presenting post-translational modifications, such as phosphorylations, acetylations and methylations, among others. On the other hand, the identification of peptides mapping to genomic regions previously annotated as non-coding has allowed to correct annotations, leading to N-terminal extension of protein sequences, and the uncovering of eight novel protein-coding genes. The alliance of proteomics, genomics and transcriptomics has resulted in a powerful combination for improving the L. infantum reference genome annotation.

If the world’s countries seriously tackle the climate targets agreed in Paris, their citizens are likely to experience substantial changes in production, consumption and employment. We present a long-run post-Keynesian model for studying the potential implications of a major transition on macroeconomic stability and employment. It is a demand-led model in which firms have considerable but not absolute freedom to administer prices, while household consumption exhibits inertia. Firms continually seek input-saving technological improvements that, in the aggregate, tie technological progress to firms' cost structure. Together with firm pricing strategies and wage setting, the productivities of different inputs determine the functional income distribution. Saving and investment, and production and purchase of consumption goods, are undertaken by different economic actors, driven by income and capacity utilization, with the possibility that productive capacity exceeds, or falls short of, effective demand. The model produces business cycles and long waves driven by technological change. We present results for a “downshifting” scenario in which households voluntarily withdraw labor and discuss the implications of downshifting for stability, growth, and employment. We contrast the downshifting scenario with ones in which households reduce consumption without withdrawing from the labor pool.

This study introduces a data obfuscation technique, leveraging the exponential map associated with the generators of Lie groups. Originating from quantum machine learning frameworks, our method illustrates the practical application of quantum mechanics principles in data processing. Specifically, it employs the exponential map of a generator algebra to introduce controlled noise into the data, achieving obfuscated data while preserving its utility for machine learning tasks. This strategy is shown to safeguard privacy in sensitive datasets, such as discussed medical records, and to enhance dataset volume and diversity through augmentation. Our empirical analysis, benchmarked against standard machine learning approaches, demonstrates that our method can maintain or even improve the predictive accuracy of the original data. This research highlights the potential of Lie group theory for advancing data privacy in medicine, marking a significant contribution to machine learning methodologies by offering the dual benefits of data obfuscation and enrichment. Through this synthesis of algebraic structures and machine learning, we propose new pathways for the secure and effective use of data in sensitive areas.

Document image binarization is a challenging task, especially when it comes to text segmentation in degraded document images. The binarization, as a pre-processing step of optical character recognition (OCR), is one of the most fundamental and commonly used segmentation methods. It separates the foreground text from the background of the document image to facilitate subsequent image processing. In view of the different degradation degree of document image, researchers have proposed a variety of solutions. This paper reviews the main binarization techniques, including both traditional algorithms and deep learning-based algorithms. We also summarize some difficulties and challenges in the field of document image binarization. Here, we evaluate various image binarization techniques to identify shortcomings in current methods and provide some help for future research.

Commercially available multispectral and thermal imagers are commonly deployed for environmental monitoring on small uncrewed aerial systems (sUAS, <55 lbs). Our team assessed the challenges of deploying these imagers on a Group 3 classification UAS (weight: 55-1320 lbs, maximum altitude: 18,000 ft MSL, maximum speed: 250 kts) for the purpose of land-atmosphere interaction studies. A Micasense Altum multispectral imager was deployed on two very similar mid-sized (Group 3) UAS, a Mississippi State University (MSU) TigerShark XP and the Department of Energy (DOE) ArcticShark. This paper examines the effects of flight on imaging systems mounted on UASs flying at higher altitudes, faster speeds, and for longer duration, which near future technology will make more the norm. For these platforms we found that the acquisition rate may need to be higher to achieve a minimum 75% overlap, as required by certain post-processing algorithms. Additionally pre-flight calibration panel referencing was found to be problematic for converting flight images to reflectance, due to the changing illumination conditions during the extended duration flights. We developed an automated workflow to correct the image frames via data from an onboard hemispherical solar sensor mounted on the top of the airframe, and we assessed these data against known spectral ground targets and independent sources. Finally, this manuscript may be used as a reference for collecting similar datasets in the future. The datasets described within this manuscript may be used as a starting point for future research.

Protein translational modifications (PTMs) generate an enormous, but as yet undetermined, expansion of the expressed proteoforms. In this Viewpoint, we firstly differentiate the concepts of proteoform and peptidoform by reviewing and discussing previous literature. We show that the current PTM biological investigation and annotation largely follow a PTM site-specific rather than proteoform-specific approach. We further illustrate a potentially useful matching strategy in which a particular “modified peptidoform” is matched to the corresponding “unmodified peptidoform” as a reference for the quantitative analysis between samples and conditions. We suggest this strategy could provide directly relevant information for learning the PTM site-specific biological functions. Accordingly, we advocate for the wider use of the nomenclature “peptidoform” in the future bottom-up proteomic studies.

The Hollow fiber membrane contactor (HFMC) is an intensification process that combines membrane and absorption technologies, being a technology in expansion, so the dynamics of this process is crucial for an increase in industrial scale-up. In this manuscript a rigorous dynamic model of an HFMC is developed and simulated in Python software for the absorption of post-combustion CO2 using a monoethanolamine (MEA) solution, which was validated using available data in literature in steady state. Dynamic simulations were performed to analyze the model's capability to predict the effect of disturbances on the responses of CO2 capture ratio and loading. Four distinct experiments were conducted by step changes and pulse disturbances at the following variables: gas and liquid volumetric flow rates, CO2 composition in flue gases, and CO2 lean load. The gas phase showed a faster response compared to the liquid. The CO2 capture ratio and rich loading presented opposite responses when disturbing both liquid flows, and for the composition and lean loading variations, the capture ratio presented an inverse response characteristic, while the loading showed a delayed response. As the model proved to be capable of returning to the reference state, it can potentially be used for control studies purposes.

An understanding of the mechanism underlying fruit ripening is critical for fruit quality improvement. Although post-harvest ethylene application is known to enhance the onset of fruit ripening, exact mechanisms remain unclear. To characterize the fruit ripening process and mechanism, we investigated the effects of exposing kiwifruit cultivars ‘Hayward’ and ‘Gamrok’ to exogenous ethylene treatment post-harvest using comprehensive proteomic analyses. Comparative two-dimensional gel electrophoresis showed that most of the proteins aggregated in ethylene-treated samples compared to the control (non-treated). We observed that among all ethylene treatments, 95 proteins from ‘Hayward’ and 106 from ‘Gamrok’ were differentially expressed. Interestingly, among the elicited protein successfully identified by matrix-assisted laser desorption/ionization tandem time-of-flight mass spectrometry, 50% from “Hayward’ and 60% from ‘Gamrok’ are associated with fruit ripening. Furthermore, 18% and 10% of proteins, respectively, are associated with defense response, whereas other major proteins are related to protein biosynthesis and photosynthesis/Calvin cycle. Interactions between identified proteins were demonstrated by bioinformatic analysis, providing insights into biological pathways and molecular functions in post-harvest kiwifruit ripening elicited by ethylene application. The present proteomic study in accordance with physiological analysis provides a quantitative evaluation of fruit ripening in response to exogenous ethylene in post-harvest kiwifruit.

With the intensification of population aging in rural areas, it becomes increasingly important to analyze the post-retirement migration intention of rural residents and the variables influencing these intentions. In this study, we focus on rural residents aged 45 to 60 and investigate the main variables that influence the post-retirement migration intention of rural residents, using survey data collected from 164 households in three different rural areas and the logistic regression model. From the result of this study, we found that gender, part-time employment, savings level, children's residence and occupation stability, and interest in urban living positively affect migration intention. In contrast, the number of rural companions, relationships with others in rural areas, and evaluation of rural living have a negative effect. In addition, we employ age and the proportion of mobile income as control variables to examine the variables that influence the post-retirement migration intention in different age groups and mobile income groups. The analysis reveals that, the variables influencing post-retirement migration intention varied across age groups and mobile income groups, and this variation can be attributed to the differences between groups' characteristics.

The depletion of the ore reserves in the world necessitates the search for secondary sources such as waste products (tailings and slag). A smelter in Namibia has historic slag which accumulated over decades of its operating life. Analytical and mineralogical characterization of the slag was performed using the X-ray fluorescence (XRF) analysis, Atomic Absorption Spectrometer (AAS), ICP-OES, scanning electron microscopy energy dispersive spectroscopy (SEM-EDS) analysis, and optical microscopy analysis. The chemical analyses showed that the metal values contained in the slag were mainly copper, lead, and zinc whose average contents were approximately 0.3%Cu, 2.4%Pb and 3.2%Zn. About 10.5%Fe was also contained in the slag. Germanium was detected by scanning electron microscopy, but was however below detection limits of the chemical analysis equipment used. Based on the results, approximate conditions under which the different slag phases were formed were estimated and the recovery routes for the various metals were proposed. Analysis by both optical and scanning electron microscopy revealed that Zn and Fe occurred mainly in association with O as oxides, while Cu and Pb were mainly associated with S as sulphides. The slag consisted of three different phases; namely the silicate phase (slag), metallic phase and the sulphide phases. The slag phases were mainly glass, silicate phases and metallic and sulphide phases. It was observed that the metallic and sulphide phases were dominant in the finer size fractions (-75 µm) whereas the sulphide phase was also present in the coarser size fractions (+300 µm). An important finding from the microscopy examination was that the sulphide phases were interstitial and could be liberated from the slag. This finding meant that liberation and subsequent concentration of the sulphide phases was feasible using conventional processing techniques.

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.

(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.

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.

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.

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.

In this paper, the effect of multi-pass friction stir processing on the mechanical properties of AZ91 alloy has been studied. For the numerical investigation, this process has been simulated with the three-dimensional numerical modeling based on the ABAQUS/Explicit. This simulation involves the Johnson-Cook models for defining the material behavior during this intense plastic deformation and investigating the fracture criterion. The tool plunging and stirring phases in the two-pass process has been simulated. To prevent too much distortion of elements during modeling, the Arbitrary Lagrangian-Eulerian technique for automatically re-meshing of distorted elements has been used. The model was calibrated using the experimental results from the previous works. This model can predict the transient temperature distribution and residual stress field during FSP on AZ91. The results show that the maximum temperature in the advancing-side region is more than that in the retreating-side region. In addition, numerical results show that at the end position of the process, the tool during the lift-up leaves the keyhole region in the compressive stress state. The experimental results investigated the effect of multi-pass FSP on the microstructure, microhardness, tensile and creep properties of AZ91 magnesium alloy. The FSP is performed by applying 50% overlapping. The tensile, and creep tests are conducted at several temperatures from 25 to 210 °C. The optical microscopy and scanning electron micrograph (SEM) were used to study the microstructure of the samples after performing multi-pass friction stir processing. The experimental results indicate that on average, the tensile strength, microhardness, and creep strength of the processed samples increased by about 29, 23, and 38 %, respectively compared to the unprocessed ones.

Background: Alongside their long-term effects - post-concussion syndrome (PCS) - mild traumatic brain injuries (mTBI) are significant public health concerns. Currently, there is a lack of reliable biomarkers for diagnosing and monitoring mTBI and PCS. Exosomes are small extracellular vesicles secreted by cells that have recently emerged as a potential source of biomarkers for mTBI and PCS due to their ability to cross the blood-brain barrier and reflect the pathophysiology of brain injury. This study aimed to investigate the role of salivary exosomal biomarkers in mTBI and PCS. Methods: A systematic review using the PRISMA guidelines was conducted, and studies were selected based on their relevance to the topic. Results: Studies have shown that exosomal tau, phosphorylated tau (p-tau), amyloid beta (Aβ), and microRNAs (miRNAs) are potential biomarkers for mTBI and PCS. Specifically, elevated levels of exosomal tau and p-tau have been associated with mTBI and PCS, as well as with repetitive mTBI. Dysregulated exosomal miRNAs have also been observed in individuals with mTBI and PCS. Additionally, exosomal Prion cellular protein (PRPc), coagulation factor XIII (XIIIa), synaptogyrin-3, IL-6, and aquaporins have been identified as promising biomarkers for mTBI and PCS. Conclusion: Salivary exosomal biomarkers have the potential to serve as non-invasive and easily accessible diagnostic and prognostic tools for mTBI and PCS. Further studies are needed to validate these biomarkers and to develop standardized protocols for their use in clinical settings. Salivary exosomal biomarkers can improve the diagnosis, monitoring, and treatment of mTBI and PCS, leading to improved patient outcomes.

Malware detection is a crucial pillar of cybersecurity and aims to identify and neutralize malware threats. This study investigates how three deep learning algorithms - Convolutional Neural Net-works with One-Dimensional Architecture (CNN1D), Neural Networks (NN), and a hybrid model of one dimensional convolutional neural networks (CNN1D) and Long Short-Term Memory (LSTM) - help detect malware in Portable Executable working (.exe) files. Using a large dataset of tagged malware and benign samples, the effectiveness of these algorithms in distinguishing dangerous from harmless executables is extensively tested. In addition, the study evaluates the computational efficiency of the proposed methods for a variety of hardware configurations, including Central Processing Units (CPU), Graphics Processing Units (GPU), Raspberry Pi (IoT device), and Tensor Processing Units (TPU). Performance metrics provide insight into the scalability and effectiveness of the model across different hardware configurations. The results of this study have significant impact on the development of malware detection, particularly in the context of IoT security. By demonstrating the capabilities and limitations of CNN1D, Neural Networks, and CNN1D with LSTM models, the study provides practitioners with efficient and scalable solutions to real-world malware detection difficulties. In addition, insights from performance tests on various hardware platforms provide important assistance in developing robust security measures in IoT contexts, strengthening cybersecurity defenses in an ever-changing digital landscape.

Long Covid is a term used for patients who have recovered from COVID-19 but exhibit persistent cognitive dysfunction, including mental confusion, difficulties in attention, impairment in executive functions and slow movements, among other common symptoms. A study was conducted with 65 patients who had a positive RT-PCR diagnosis and reported symptoms of cognitive impairment, such as memory loss and attention difficulties after recovery. The patients underwent neuropsychological evaluation and completed questionnaires on cognition, mood, and quality of life. During the cognitive screening, 71% of the patients showed alterations, with deficits in visual memory (69%), language (54%), visuospatial construction (49%), verbal episodic memory (37%), executive functions (36%), attentional abilities (34%), and premorbid intelligence (12%). It is important to highlight the need for treatments and further studies to understand the long-term side effects of this disease.

Classical religious texts remain an essential part of human culture due to their undiminished influence on the advancement of civilization. Although their entirely divine origin is questioned repeatedly, explicit or implicit quoting and adherence to their basic guidelines are fundamental in modern society. In this respect, these documents’ inner structure and linguistic style appear to be pivotal. This paper considers the topic from the standpoint of small textual patterns classified using deep learning methods, traditionally applied to analyze short textual material like tweets. We divide the considered documents into small sequential chunks imitating tweets and categorizing them, classifying an entire text. The proposed method demonstrates that the religious text collections correspond to stable ”Twitter”-like structures that adequately reflect stylistic properties. So, concise word combinations seem to be an inborn textual attribute that adequately outlines the proposed multi-source authorship. This approach differs from traditional methods of analyzing classical religious documents, which are based on the consideration and interpretation of relatively long templates. The case study consists of three famous collections of Mosaic authorship in the Old Testament (Hebrew), Pauline authorship in the New Testament (Greek), and Al-Ghazali authorship (Arabic). The obtained results go well with most previously expressed evaluations and complement them with new implications, particularly in the authorship of two famous manuscripts attributed to Al-Ghazali.

Knowledge of post-larval swordfish (Xiphias gladius) ecology in the world’s oceans is incomplete as they are rarely found in ichthyoplankton samplings or commercial catches and individuals are difficult to observe in the marine ecosystem. Analyses of stomach contents of apex predators can provide otherwise unobtainable ecological insights. Two well-preserved bills of post-larval swordfish were identified among the partially digested stomach contents of an adult male dolphinfish (Coryphaena hippurus) caught in the northern Tyrrhenian Sea. The lower jaw to fork lengths of the two predated swordfish were estimated at respectively, 18 and 22 cm, corresponding to 81- and 99-day-old swordfish hatched in the 2022 spawning season. This analysis and recent information on the reproductive dynamics of swordfish in the same area reported in the literature shed light not only on the early stages of swordfish growth but also on dolphinfish ecology in the Tyrrhenian Sea. The two species share the same habitat and are both caught with commercial pelagic surface longlines. Environmental shifts associated with climate change could unpredictably modify the reproduction dynamics, growth, recruitment and distribution of both species. This knowledge is important for the sustainable management of regional fisheries.

Soil microbiome plays key role in plant health. Native soil microbiome inoculation, metagenomic profiling and high-throughput cultivation require efficient microbe extraction. The sonication and oscillation are most common methods to extract soil microbiome. However, the extraction efficiency of those methods has barely been investigated. Here, we compared the culturable microbe numbers, community structures and alpha diversities among the methods including sonication, oscillation, centrifugation and their processing time. The results showed that, sonication significantly increases culturable colony number compare with oscillation and centrifugation factors. Furthermore, sonication strategy shows a main factor influence extraction efficiency, but increased sonication time can recovery this impact. Finally, processing times of extraction show a significant negative relationship with α diversity among extracted microbiota. In conclusion, sonication is a main factor for enrich in-suit microbiota, and increased extraction time significantly decrease α diversity of extracted microbiota. These results can provide insights into the isolation and utilization of microorganism source.

Conventional MRI sequences are standard methods to monitor patients with brain tumors but have significant limitations especially after irradiation. Currently, the role of FET-PET in radiotherapy of glioblastoma is emerging, starting from target definition, response assessment and in distinguishing progression from post-irradiation changes. Recently a PET RANO criteria have been published providing optimal strategy for treatment evaluation with amino-acid PET. Earlier, a PET/RANO group reported contribution of PET imaging to radiotherapy planning and monitoring in glioma patients. Also, increasing evidence have showed advantages of amino-acid PET vs. RANO MRI for prediction of overall survival. In this narrative review we aimed to summarize published data on FET-PET based treatment response assessment to radiotherapy and focused on details in protocols.

Speech signals are degraded in real-life environments, product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One of the conditions that make adverse quality difficult to handle in those systems is reverberation, produced by sound wave reflections that travel from the source to the microphone in multiple directions.To enhance signals in such adverse conditions, several deep learning-based methods have been proposed and proven to be effective. Recently, recurrent neural networks, especially those with long and short-term memory (LSTM), have presented surprising results in tasks related to time-dependent processing of signals, such as speech. One of the most challenging aspects of LSTM networks is the high computational cost of the training procedure, which has limited extended experimentation in several cases. In this work, we present a proposal to evaluate the hybrid models of neural networks to learn different reverberation conditions without any previous information. The results show that some combination of LSTM and perceptron layers produce good results in comparison to those from pure LSTM networks, given a fixed number of layers. The evaluation has been made based on quality measurements of the signal's spectrum, training time of the networks and statistical validation of results. Results help to affirm the fact that hybrid networks represent an important solution for speech signal enhancement, with advantages in efficiency, but without a significan drop in quality.

This study aims to clarify the influence of photographic environments under different light sources on image-based SPAD value prediction. Radish leaf patches of 1.5 cm diameter were photographed under halogen or LED light. The input variables for the SPAD value prediction using random forests were RGB values, HSL values, and HSV values. Additionally, the light color temperature (LCT) and illuminance (ILL) were used as the input variables. Model performance was assessed using Pearson’s correlation coefficient (COR), Nash-Sutcliffe efficiency (NSE), and root mean squared error (RMSE). SPAD value prediction resulted in high accuracy in a stable light environment; CORRGB+ILL+LCT and CORHSL+ILL+LCT were 0.929 and 0.922, respectively. Image-based SPAD value prediction was effective under halogen light with a similar color temperature at dusk; CORRGB+ILL and CORHSL+ILL were 0.895 and 0.876, respectively. The HSL value under LED could be used to predict the SPAD value with high accuracy; COR, NSE, and RMSE were 0.972, 0.944, and 2.07, respectively. The partial dependence plots of the H value indicate a change from blue to green with increasing SPAD values. Further studies are required to examine this method under outdoor conditions in spatiotemporally dynamic light environments.

Fasting, a practice with historical roots in various cultures, has recently garnered significant interest in the field of medicine. In this article, we delve into the mechanisms underlying fasting-induced autophagy and its therapeutic applications for spike protein associated pathology. We explore the therapeutic potential of fasting on spike protein-related pathology. Additionally, we discuss factors that affect fasting, such as duration, type (dry vs. water), and the role of specific compounds like spermidine, resveratrol, rapamycin, and metformin. Furthermore, we analyse the interactions between fasting and other practices such as exercise, and highlight important considerations regarding participant characteristics, including pregnancy, breastfeeding, medication interactions, and metabolic disorders. In conclusion, fasting, coupled with an understanding of its nuances, holds promise as a therapeutic intervention with broad implications for human health.

Post-stroke depressive disorders (PSD) and post-stroke cognitive impairments (PCI) are frequent consequences of ischemic stroke (IS). The study was focused on exploring possible associations between relative volumes of cortical and limbic brain structures during the acute period of IS, and changes in biochemical indices of hypothalamic-pituitary-adrenal, sympathoadrenal medullary and inflammatory systems, with the development of PSD or PCI after mild or moderate IS. Patients developing PSD later on had significantly smaller relative volumes of the hippocampus, entorhinal cortex, and temporal pole versus patients without depressive symptoms. PCI development was associated with significantly smaller volumes of temporal pole and supramarginal gyrus versus patients without cognitive changes. Multiple logistic regression analysis showed higher likelihood of developing PSD in patients with smaller temporal pole volume (β0=10.9; β=-4.27; p=0.04) and increased salivary α-amylase activity (β0=-3.55; β=2.68e-05; p=0.02,). PCI likelihood was higher in patients with smaller supramarginal gyrus volume (β0=3.41; β=-0.99; p=0.047), smaller temporal pole volume (β0=3.41; β=-3.12; p=0. 06), and increased hair cortisol concentration at admission (index of accumulated stress load within a month before IS; β0=3.41; β=-0.05; p=0.08). The data support the hypothesis suggesting predisposition to PSD and PCI and multi hit scenarios of their pathogenesis with IS providing a final hit.

Obesity entails metabolic alterations across multiple organs, highlighting the role of inter-organ communication in its pathogenesis. Extracellular vesicles (EVs) are communication agents in physiological and pathological conditions and although they have been associated with obesi-ty-comorbidities, their protein cargo in this context remain largely unknown. To decipher the messages encapsulated in EVs, we isolated plasma derived EVs from diet induced obese murine models. Obese plasma EVs exhibited a decline in protein diversity while control EVs revealed significant enrichment in protein folding functions, highlighting the importance of proper folder in maintaining metabolic homeostasis. Previously, we revealed that gut derived EVs proteome holds particular significance in obesity. Here, we compared plasma and gut EVs and identified four proteins exclusively present in the control state of both EVs, revealing the potential for a non-invasive assessment of gut health by analyzing blood derived EVs. Given the relevance of post-translational modifications (PTMs), we observed a shift in chromatin-related proteins from glycation to acetylation in obese gut EVs, suggesting a regulatory mechanism targeting DNA transcription during obesity. This study provides valuable insights into novel roles of EVs and protein post-translational modifications in the intricate mechanisms underlying obesity, shed-ding light on potential biomarkers and pathways for future research.

Apoptosis is associated with numerous phenotypical characteristics, and is thus studied with many tools. In this study, we compared two broadly used apoptotic assays: TUNEL and staining with an antibody targeting the activated form of an effector caspase. To compare them, we developed a protocol based on commonly used tools such as filters, zprojection and thresholding. Even though it is commonly used in imageprocessing protocols, thresholding remains a recurring problem. Here we analyzed the impact of processing parameters and readout choice on the accuracy of apoptotic signal quantification. Our results show that TUNEL is quite robust, even if image processing parameters can allow or not to detect subtle differences of the apoptotic rate. On the contrary, images from anticleaved caspase staining are more sensitive to handle and proved to necessitate to be processed more carefully. We then developed an open source Fiji macro automatizing most steps of the image processing and quantification protocol. It is noteworthy that the field of application of this macro is wider than apoptosis as it can perfectly be used to treat and quantify other kind of images.

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO2 emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control.

Our research aims to address the urgent need for retrofitting measures to enhance the resilience of damaged coupling beams in real-life scenarios. We conducted a series of tests on scaled-down prototype coupling beams, carefully adhering to similarity theory requirements to ensure accurate representation. The test results showed that the chord rotation capacities of different specimens with the same diagonal bundle varied significantly due to the difference in the confinement levels. The specimens with lower level of confinement were found to have less displacement capacity. When the specimens were strengthened by wrapping with GFRP after damage, it was observed that the increase in confinement level significantly increased the chord rotation capacities of all specimens. In addition, in the tests before the strengthening, the elongation behavior of the specimens is observed until the damage development reaches approximately 2% chord rotation. With the in-crease in chord rotation, the elongation behavior of the specimens stops with increasing damage and then shortening behavior is observed. After retrofitting, it was observed that the axial elongation continued in a limited manner depending on the location and size of the concrete separated from the beam core in the case of collapse before strengthening, and then the beam showed a shortening behavior predominantly. After strengthening studies, our findings contribute valuable insights into the behavior and performance of damaged coupling beams, emphasizing the potential of urgent GFRP wrapping as a viable solution to enhance the seismic resilience of middle- and high-class buildings with structural walls after seismic events.

Text fields in electronic medical records (EMR) contain information on important factors that influence health outcomes, however, they are underutilized in clinical decision making due to their unstructured nature. We analyzed 6,497 inpatient surgical cases with 719,308 free text notes from Le Bonheur Children’s Hospital EMR. We used a text mining approach on preoperative notes to obtain the text-based risk score algorithm as predictive of death within 30 days of surgery. We studied the additional performance obtained by including text-based risk score as a predictor of death along with other structured data based clinical risk factors. The C-statistic of a logistic regression model with 5-fold cross-validation significantly improved from 0.76 to 0.92 when text-based risk scores were included in addition to structured data. We conclude that preoperative free text notes in EMR include significant information that can predict adverse surgery outcomes.

The incidence of cancer in organ transplant patients is higher than in the non-transplanted population. The incidence increases with increasing age. The use of Fludeoxyglucose positron emission tomography/CT (PET/CT) is sensitive and specific to detect PTLD LD compared with conventional CT imaging. We analyzed the medical data of 127 patients aged over 60 years, who underwent heart transplantation in the above period, who have been practicing early CT-PET for diagnostic purposes between February 2007 and October 2018. Of 127 consecutive patients who underwent CT-PET, SUVs up than 4, were found in 84 patients of which 20 were affected by PTLDs, seven patients were affected by chronic non neoplastic inflammatory diseases, the remainder were affected by other neoplasms. The favorable effect of physical activity programs on cardiorespiratory and psychomotor function occur in all patients. In conclusion, CT-PET at the first doubts about the possibility of the development of neoplasms has allowed a diagnosis and then a treatment more quickly. Education in behavioral norms that improve the patient's quality of life is necessary.

Objectives: To develop a machine learning-based model for the identification of features involved in the prediction of long-term erectile dysfunction (ED) after COVID-19 recovery. Methods: We performed an observational prospective multicentre study. Participants were divided into 2 groups: I) Patients with a past history of COVID-19; II) Patients without a previous microbiological diagnosis of COVID-19. A total of 361 patients (COVID-19 group, n=166, Control group; n=195) were assessed from January 2022 to March 2023. COVID-19 group patients were assessed 12 months after COVID-19 recovery; Control group patients were assessed within the same time window. The primary outcome measure was ED. A machine learning-based model including three algorithms (random forest, logistic regression and support vector machines [SVM]) was applied to perform the automatic selection of those features involved in the prediction of ED. The algorithm SVM-recursive feature elimination (RFE) was also executed. Results: The median age was 55 years in both groups. The final selection of variables in our model was: group, SARS-CoV-2 vaccination status, hypertension, diabetes, beta blocker treatment, antiplatelet therapy and coffee intake. The algorithm SVM-RFE showed that a past history of COVID-19 and SARS-CoV-2 vaccination were both long-term ED predictors in our model. Conclusions: We developed a machine learning-based model for the prediction of long-term ED following COVID-19 recovery. A past history of COVID-19 and SARS-CoV-2 vaccination were both predictors in our model. The application of our predictive tool in a community setting could avoid the adverse effects of ED and the unfavourable economic impact associated.