This article delves into the enduring relevance of Liberal International Relations (IR) Theory amidst persistent criticisms regarding power dynamics and its applicability in emerging states. Despite its detractors, Liberal IR Theory offers a nuanced understanding of state behavior, blending social contexts with power dynamics. It recognizes the intricacies of economic interdependence and advocates for a balanced approach in advancing democracy and human rights. While nationalism poses challenges to international institutions, their adaptability endures. Leaders, albeit constrained, retain the capacity to foster peace through visionary leadership and global cooperation. By acknowledging its limitations and fostering open dialogue, Liberal IR Theory continues to evolve, poised to contribute to a just and peaceful global order.

Agriculture contributes towards South African economy, but this sector is highly vulnerable to risks imposed by climate change. Smallholder maize farmers are specifically susceptible to climate change impacts. Maize crop plays a crucial role in the country's food security as it is considered a stable food for households and source of feed for livestock. The study aimed to analyze the socio-economic factors influencing smallholder maize farmers’ willingness to adopt climate-smart agriculture. It was conducted in three different areas due to their specific agro-ecological zones. Multipurpose research design was used to gather data, and multistage random sampling to choose the study areas. Subsequently, 209 purposively selected farmers were interviewed face-to-face using structured questionnaires and focus discussion groups. Descriptive statistics and Double-hurdle regression model were used to analyze the data. Descriptive results indicated that 81%, 67%, and 63% farmers were willing to adopt CSA in Ga-Makanye, Gabaza, and Giyani, respectively. Empirical results from the first and second hurdles of the regression analysis showed that farmers’ education, crop diversification, information about CSA positively influenced the decision to adopt CSA while household size and agricultural experience negatively influenced the decision to adopt CSA. It is recommended that the Department of Agriculture, Land Reform, and Rural Development should provide CSA workshops and educational programs to farmers to enhance their knowledge and decision-making processes regarding adaptation strategies.

: Microplastics and nanoplastics (MNPs) are becoming an increasingly severe global problem due to their widespread distribution and complex impact on living organisms. Apart from their environmental impact, the effects of MNPs on living organisms have also continued to attract attention. The harmful impact of MNPs has been extensively documented in marine invertebrates and larger marine vertebrates like fish. However, the research on the toxicity of these particles on mammals is still limited, and their possible effects on humans are poorly understood. Considering that MNPs are commonly found in food or food packaging, humans are primarily exposed to them through ingestion. It would be valuable to investigate the potential harmful effects of these particles on gut health. This review focuses on recent research exploring the toxicological impacts of micro- and nanoplastics on the gut, as observed in human cell lines and mammalian models. Available data from various studies indicate that the accumulation of MNPs in mammalian models and human cells may result in adverse consequences, in terms of epithelial toxicity, immune toxicity, and disruption of gut microbiota. The paper also discusses the current research limitations and prospects in this field, aiming to provide a scientific basis and reference for further studies on the toxic mechanisms of micro- and nanoplastics.

The Simulation analogy presented in this work enhances the accessibility of abstract quantum theories, specifically the stochastic hydrodyanimc model (SQHM), by relating them to our daily experiences. The SQHM incorporates the influence of fluctuating gravitational background, resembling dark energy, into quantum equations. This model successfully addresses key aspects of Objective-Collapse Theories, including resolving the 'tails' problem through the definition of quantum potential length in addition to the De Broglie length, beyond which coherent Schrödinger quantum behavior and wavefunction tails cannot be maintained. The SQHM emphasizes that an external environment is unnecessary, asserting that the quantum stochastic behavior leading to wave-function collapse can be an inherent property of a system in a spacetime with fluctuating metrics. Embedded in relativistic quantum mechanics, the theory establishes a coherent link between the uncertainty principle and the constancy of light speed, aligning seamlessly with finite information transmission speed. Within a fluctuating quantum system, the SQHM derives the indeterminacy relation between energy and time, offering insights into measurement processes impossible within a finite time interval in a truly quantum global system. Experimental validation is found in confirming the Lindemann constant for solid lattice melting points and the transition from fluid to superfluid states. The SQHM's self-consistency lies in its ability to describe wavefunction collapse and the measure process. Additionally, the theory resolves the Pre-existing Reality problem by showing that large-scale systems naturally decay into decoherent states stable in time. Continuing, the paper demonstrates that the physical dynamics of SQHM can be analogized to a computer simulation employing optimization procedures for realization. This perspective elucidates the concept of time in contemporary reality and enriches our comprehension of free will. The overall framework introduces an irreversible process impacting the manifestation of macroscopic reality at the present time, asserting that the multiverse exists solely in future states, with the past comprising the formed universe after the current moment. Decoherence at the present time functions as a reduction of the multiverse to a single universe. The macroscopic reality, characterized by fractal consistency where microscopic domains with quantum properties coexist, provides insights into how our consciousness apprehends dynamic reality, the spontaneous emergence of gravity in discrete spacetime evolution, and the attainment of the classical General Relativity limit in Quantum Loop Gravity and Causal Dynamical Triangulation. The Simulation Analogy highlights a strategy focused on minimizing information processing, facilitating the universal simulation in solving its predetermined problem. From within, reality becomes the manifestation of specific physical laws emerging from the inherent structure of the simulation devised to address its particular issue. In this context, the reality simulation appears to employ an entropic optimization strategy, minimizing information loss while efficiently compressing data in line with the simulation's intended purpose.

Background: After the increasingly common anterior cruciate ligament reconstruction (ACLR) procedure in competitive athletes, rehabilitation is crucial for facilitating a timely return to sports (RTS) and preventing re-injury. This pilot study investigates the biomechanical and psychological outcomes of postoperative rehabilitation in competitive athletes, comparing supervised rehabilita-tion (SVR) and home-based rehabilitation (HBR). Methods: After ACLR, 60 (out of 74 screened) athletes were recruited and equally divided into 2 groups using non-probability convenience sam-pling: 30 HBR and 30 SVR (each group comprising 15 males and 15 females). Rehabilitation out-comes in respective groups were evaluated at 8 months using measures (Tegner-Activity-Scale [TAS], International Knee Documentation Committee subjective knee form [IKDC-SKF], ACL Return to Sport after Injury [ACL-RSI]) and objective parameters (isometric muscle strength, hamstring/quadriceps asymmetry). RTS was evaluated at 9 months; with ACL re-injury rates rec-orded approximately 6 months post-RTS. Results: Both groups exhibited decreased TAS scores (HBR: 8 to 6, SVR: 8 to 7), with the SVR group demonstrating superior post-operative IKDC-SKF scores (81.82 vs. 68.43) and lower ACL-RSI scores (49.46 vs. 55.25). Isometric and isokinetic mus-cle strength, along with asymmetry values, favored the SVR group 8 months post-ACLR (p

The oral mucosa represents a defense between the external environment and the rest of the body and encompasses several antimicrobial and antiviral mechanisms. Oral mucosal cells are constantly bathed in hypotonic saliva (normally one-third tonicity compared to plasma) and are repeatedly exposed to environmental stresses of tonicity, temperature and pH by the drinks we imbibe (e.g. hypotonic: water, tea, coffee; hypertonic: assorted fruit juices, red wines), as well as of diverse microbial and viral flora. In the mouth, the broad-spectrum antiviral mediator MxA (a dynamin-family large GTPase) is constitutively expressed in healthy periodontal tissues, and also induced by Type III interferons (e.g. IFN-λ1). Endogenously induced human MxA and exogenously expressed human GFP-MxA formed membraneless biomolecular condensates in the cytoplasm of oral carcinoma cells (OECM1 cell line). These condensates likely represent storage granules in equilibrium with antivirally active dispersed MxA. Remarkably, cytoplasmic MxA condensates were exquisitely sensitive sensors of hypotonicity – the condensates in oral epithelium disassembled within 1-2 min of exposure of cells to saliva-like one-third hypotonicity, and spontaneously reassembled in the next 4-7 min. OECM1 cells preloaded with calcein-AM (a reporter of cytosolic “macromolecular crowding”) confirmed unquenching and then requenching of calcein fluorescence during this process. Hypertonicity had little effect on MxA condensates. The spontaneous reassembly of GFP-MxA condensates in oral epithelial cells even under continuous saliva-like hypotonicity was slowed by the protein phosphatase inhibitor cyclosporin A (CsA) and by the K-channel blocker tetraethylammonium chloride (TEA) suggestive of the involvement of the volume-sensitive WNK kinase-protein phosphatase (PTP)-K-Cl cotransporter (KCC) pathway in the regulated volume decrease (RVD) during condensate reassembly in oral cells. Thus, physiologically, hypotonic drinks (water, tea, coffee) trigger a rapid deployment of antiviral MxA throughout the cytoplasm of oral epithelial cells, with subsequent salvage of MxA back into storage granules/condensates.

Background: Feline infectious peritonitis (FIP) is a fatal feline disease classified as either effusive (‘wet’), non-effusive (‘dry’), or a mixture of both forms (‘mixed’). The anti-FIP therapeutic effect of Mutian and molnupiravir, two drugs whose active ingredient is a nucleic acid analog, has been confirmed recently. Methods: Of the cats with FIP, we observed a total of 122 and 56 cases achieved remission after administration of Mutian and molnupiravir as routine treatments, respectively. Changes in clinical indicators suggested to be correlated with FIP remission (weight, hematocrit, and albumin to globulin ratio) before and after the administration of each drug and during follow-up observation were statistically compared for each FIP type. Results: In all three FIP types, administration of either Mutian or molnupiravir resulted in statistically significant increases in these indicators. Furthermore, the effect of Mutian on improving the albumin to globulin ratio was not observed at all in wet FIP, as compared with that of molnupiravir, but statistically significant in mixed and dry (P<0.02 and P<0.003, respectively). These clinical features were all due to differences in fluctuations of circulating globulin levels. Conclusions: These results indicate slight inflammatory responses might be elicited continuously by residual feline coronavirus non-disappeared through molnupiravir treatments.

Soybean a pulse of considerable nutritional value due to its high protein, fibers and polyunsaturated fatty acid (PUFA) contents, also contains phytoestrogenic compounds that definitely hinder its recommendation for general consumption. Contrarily to ancient times when soybeans were boiled, modern commercial soy-foods can contain up to 150 mg/100g of estrogenic isoflavones. Interestingly, current estimations of isoflavone intake in the literature do not distinguish between the origins of soy-food i.e. home-made or commercial. As a result, the isoflavone exposure in Asian countries may well be over-estimated. This study aims to demonstrate, based on step-by-step monitoring of isoflavones, that traditional and domestic treatments, leveraging isoflavones water-solubility, can indeed significantly reduce their content in soy-foods. Indeed, when compared to commercial foods, the isoflavone contents was found to be 20, 2.6, 4.5 and 9.8 times lower in “home-made” soy-juice, tofu, tempeh and miso, respectively. Additionally, water soaking was found to reduce the isoflavones levels in soy-textured-proteins by more than 70%. Hence, this simple process has the potential to help drastically reduce overall xenoestrogens exposure. This study could serve as a basis for establishing the isoflavones Reference Dose and issuing food safety guidelines.

In the process of climate change mitigation and adaptation, the focus on climate risks driven by transition innovations has received widespread attention from governments, regulators and investors. Based on the identification of low-carbon patents through the Green and Low-carbon Technology Inventory in China, we construct low-carbon innovation measurements of listed firms in China from 2015 to 2021 then an empirical model is used to investigate the impact and mechanism of climate transition innovations on the default risk. The baseline regression model shows that low-carbon innovations can mitigate the default risk of firms. Moreover, our findings are supported by instrumental variable regressions that use time costs of innovation. In addition, the mediation effect demonstrates that investor attention, total factor productivity, and technology spillovers are paths for transition innovations to affect the default risk. This study reveals that low-carbon technological advances have a positive effect on climate transition risks. Further, it provides empirical evidence for listed companies to develop low-carbon innovations.

Rare earth elements (REEs) are a type of new material resources, which have attracted significant attention in recent years. REEs have emerged as essential metals in modern-day technology due to their unique functions. Long-term large-scale mining and utilization of rare earths have caused serious environmental pollution and constitutes a global health issue, which raised concerns about human health safety. However, the toxicity profile of suspended particulate matter of REEs in the environment interacts with the human body in remain largely unknown. Studies have shown that REEs can enter the human body through a variety of pathways, leading to a variety of organ and system dysfunctions through changes in genetics, epigenetics, and signaling pathways. Through an extensive literature search and critical analysis, we provide a comprehensive overview of the available evidence, identify knowledge gaps, and make recommendations for future research directions.

To satisfy the interests of multiple agents and those of comprehensive indicators such as peak-to-valley differences and load fluctuations occurring on the network side, this paper presents a flexible load demand-side response optimization method that considers the benefits of peak-to-valley smoothing. First, load aggregation modelling of air conditioning and electric vehicles was conducted, and the complementarity of the power consumption behaviour of different types of flexible loads was used to improve the responsiveness of the load aggregator. Second, considering demand-side responses and taking into account the interests of both supply and demand, the load fluctuation and peak-to-valley difference on the network side are reduced, and a flexible load double-layer optimization model incorporating the peak-to-valley smoothing benefit is established. Finally, the effectiveness of the proposed optimization model is verified by using the KKT condition and the big M method to evaluate this two-layer optimization problem as a single-layer optimization problem. Comparative examples demonstrate that the proposed two-layer optimization method can improve the revenue of the distribution network operators and the load aggregators by using the complementary nature of the load response characteristics of electric vehicles and air conditioners. Moreover, the proposed method can effectively reduce the load peak-to-valley difference and load fluctuation of the distribution network by introducing the peak-to-valley smoothing benefit model.

The current paper provides a cutting-edge information data length- theoretic approach to human emotions. This is a revolutionary breakthrough that unifies information data length and the dynamics of emotions. The significant impact of both time and its mean value associate on both the upper and lower bounds of the obtained information data length is observed and noted. The paper concludes with some challenging open problems, combined with concluding remarks and future research pathways.

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

Biomaterials play an important role in the development of advancing three dimensional (3D) in vitro skin models, providing valuable insights for drug testing and tissue-specific modeling. Commercial materials, such as collagen, fibrin or alginate, have been widely used in skin modelling. However, they do not adequately represent the molecular complexity of skin components. On this regard, the development of novel biomaterials that represent the complexity of tissues are becoming more important in the design of advanced models. In this study, we have obtained aged human decellularized dermal extracellular matrix (dECM) hydrogels extracted from cadaveric human skin and demonstrated their potential as scaffold for advanced skin models. These dECM hydrogels effectively reproduce the complex fibrillar structure of other common scaffolds, exhibiting similar mechanical properties, while preserving the molecular composition of the native dermis. It is worth noting that fibroblasts embedded within human dECM hydrogels exhibit behavior more representative of natural skin compared to commercial collagen hydrogels, where uncontrolled cell proliferation leads to material shrinkage. The described human dECM hydrogel is able to be used as scaffold for dermal fibroblasts in a skin aging on chip model. These results demonstrate that dECM hydrogels preserve essential components of the native human dermis making them a suitable option for the development of 3D skin aging models that accurately represent the cellular microenvironment, improving existing in vitro skin models and allowing for more reliable results in dermatopathological studies.

Aim: To investigate inflammation indices and erythropoietin (EPO) levels for their potential role in distinguishing polycythemia vera (PV) from secondary polycythemia (SP), and to compare different parameter combinations in terms of diagnostic accuracy. Methods: This retrospective cohort was created from patients assessed for polycythemia from January 2020 to December 2023. PV diagnosis was made according to the 2016 WHO criteria (n=145). Those who did not fulfill the criteria were defined as having SP (n=84). Results: NLR, PLR and SII were significantly higher in the PV group (p

Taekwondo has evolved from a traditional martial art into an official Olympic sport. This study introduces a novel action recognition model tailored for Taekwondo unit actions, utilizing joint motion data acquired via wearable inertial measurement unit (IMU) sensors. The utilization of IMU sensor-measured motion data facilitates the capture of the intricate and rapid movements characteristic of Taekwondo techniques. The model, underpinned by a conventional convolutional neural network (CNN)-based image classification framework, synthesizes action images to represent individual Taekwondo unit actions. These action images are generated by mapping joint motion profiles onto the RGB color space, thus encapsulating the motion dynamics of a single unit action within a solitary image. To further refine the representation of rapid movements within these images, a time-warping technique was applied, adjusting motion profiles in relation to the velocity of the action. The effectiveness of the proposed model was assessed using a dataset compiled from 40 Taekwondo experts, yielding remarkable outcomes: an accuracy of 0.998, precision of 0.983, recall of 0.982, and an F1-score of 0.982. These results underscore the time-warping technique's contribution to enhancing feature representation, as well as the proposed method's scalability and effectiveness in recognizing Taekwondo unit actions.

Lynch syndrome (LS) is an inherited cancer predisposition disorder associated with an elevated risk of various epithelial cancers. Despite sharing the same pathogenic variant (PV), Lynch syn-drome variant heterozygotes (LSVH) exhibit considerable phenotypic variability in cancer risk. The role of Human Leukocyte Antigen (HLA) in modifying cancer risk prompted our investiga-tion into whether HLA variations act as genetic modifiers influencing age at cancer diagnosis in a unique cohort of LSVH carrying a PV in the hMLH1 gene in South Africa. Within our extensive LS cohort, 426 individuals carried the same hMLH1 PV (MLH1:c.1528C>T). We selected 100 indi-viduals with the greatest diversity in age at cancer diagnosis and the oldest unaffected individu-als for high-throughput HLA genotyping of 12 HLA class I and II loci using next-generation se-quencing. Statistical analyses employed Kaplan-Meier survival analyses with Logrank tests and Cox proportional hazards. Following the robust application of statistical correction methods, six HLA alleles (3.2%) were significantly associated with a young age at cancer diagnosis. Notably, HLA-B*15:17 and HLA-DPB1*55:01 correlated significantly with very young colorectal cancer (CRC) diagnosis (Mean age: 21y [17-25]; HR = 71.59; q

The benefits of cycling as a sustainable transportation mode are widely recognized. Cycling to work offers numerous advantages for individuals, employers, the environment, and society, ranging from improved physical health, wellbeing, and productivity to enhanced public health and reduced carbon emissions. Many governments around the world have implemented various policy measures, interventions, and initiatives to promote cycling. Some cities and towns have encouraged workplaces to provide bike-friendly amenities, such as secure bike parking/storage and shower and changing facility (referred to as end-of-trip facilities), to accommodate cyclists and motivate more employees to embrace sustainable transportation options. However, the presence or absence of such amenities has been found to both positively influence cycling behavior or deter some individuals from cycling to work. Despite the desirability of these amenities, the number of office buildings equipped with bike storage and shower/changing facility remains small, and their economic value is not well understood. In this paper, we aim to investigate whether the presence of cycling-supportive facilities could add value to office buildings. Specifically, we conduct a study using data from office buildings across England as of the end of 2021. We employ hedonic techniques to examine whether office buildings with bike storage and/or shower facility command a rent premium and whether the existence of a rent premium for bike storage and/or shower facility vary by location and across regions in England, independently from any premium associated with BREEM certification. We find that the buildings with bike storage and shower facility secure rent premiums respectively. The level of rent premiums varies with location and regions. The variations of premium are driven by the shortage of the supply of these facilities.

A new trend in cow's milk has emerged in the market called type A1 and A2 milk. These products have piqued the interest of both consumers and researchers. Recent studies suggest that A2 milk may have potential health benefits, which is why researchers are investigating this product further. It is interesting to note that the A1 and A2 milk types have area-specific characteristics compared to breed-specific characteristics. Extensive research has focused on milk derivatives obtained from cow’s milk, primarily through in vitro and animal studies. However, few clinical studies have been conducted in humans, and the results have been unsatisfactory. New molecular techniques for identifying A1 and A2 milk may help researchers to develop new studies that can clarify certain controversies surrounding A1 milk. It is essential to exercise extreme caution when interpreting the updated literature. It has the potential to spread panic worldwide and have negative economic implications. Therefore, this study aims to investigate the new aspects of A1 and A2 milk in different research areas and clarify some aspects regarding these two types of milk.

The existence of low-cost and accurate tools that can equip the First Responders (FRs) to detect trapped victims and provide insights about their health condition in the aftermath of a disaster, is imperative. To address the problem of detecting trapped victims behind walls or debris, we have developed a tool that exploits an Ultra-Wide Band (UWB) radar sensor for data collection and Machine Learning (ML) algorithms for data analysis. To evaluate the efficacy of our approach, we collected data from nine humans, both in standing and lying down positions. Next, we applied various ML algorithms to the collected dataset for two discrete sub-tasks that are of interest from an FR’s perspective. The first task is the detection of the victim’s presence, where the algorithms attained more than 95% accuracy and F1-Score. The second task is the estimation of the distance between the radar sensor and the victim, where the tool showed an average error of less than 40 cm.

The global craft beer market is witnessing substantial growth, with a particular spotlight on sour beers. These unique brews are created through lactic fermentation initiated by lactic acid bacteria (LAB). However, the presence of hops, renowned for their antimicrobial properties, can pose a limitation within the realm of sour beer production. This research aims to explore and assess the potential of sour beer as a probiotic beverage. It involves a comparative analysis of the viability of Lacticaseibacillus paracasei subsp. paracasei F19 (F19) and 431 (L431) in a sour beer with an International Bitterness Unit (IBU) value of 26.65, alongside examining the ex-pression of genes such as horA, horB, horC, hitA, bsrA, and recA, which are associated with hop resistance. The study encompasses the development of two formulations of sour beers characterized by both high hop content and a robust probiotic count (8.44 – 8.77 log CFU/mL). The findings suggest that both probiotic strains of F19 and L431, are well-suited to produce sour beers with elevated hop levels, demonstrating excellent stability. Notably, the expression of genes responsible for hops resistance exhibited distinct modulation patterns among the two strains. It appears that a higher concentration of bsrA, as observed in strain L431, may be more effective in mitigating the effects of hop-related stress, potentially surpassing the combined expression of horA and bsrA. Nonetheless, further research is essential to validate this observation in gene expression. F19 and L431 emerge as promising candidates for the development of sour beers with increased hop intensity.

The 2020 revision of South Korea’s Personal Information Protection Act (PIPA) updated procedures for the use of medical data for research. The PIPA provision allowing “pseudonymized information” to be used without the consent of the data subject for scientific research introduced ambiguity regarding the applicability of the PIPA versus the Bioethics and Safety Act (BSA), which allows “anonymized information” to be used for research only after data-subject consent and IRB approval for human-subject research are obtained. The main points requiring clarification include the distinction between “human-subject” and “scientific” research, the definition of anonymization and pseudonymization, the requirements for data-subject consent, and the procedures for institutional review boards (IRBs) and data review boards (DRBs). After reviewing the legal concepts and processes, this article recommends clarification of the guidelines for the use of medical data in research by distinguishing the concept and, in the long run, categorizing medical data based on the degree of risk.

The aim of the research was to determine the most productive tree cutting methods and the factors influencing them in flat and sloping terrain in tree plantations in Brazil. The study utilized drone-captured video material from eucalyptus and pine plantations harvesting operations. In both terrains, two cutting methods were compared, differing in the felling to the side method used: either at the edge of the harvesting front or inside. In addition, on flat terrain, the efficiency of forward felling was studied in relation to the aforementioned methods. In slope terrain, the machines were also equipped with a winch assistance system. Statistical tests were used to determine the most productive cutting methods by analyzing differences in productivity. With an average tree size of 0.3 m3, cutting productivity was 45 m3/E0h in pine cuttings and 55 m3/E0h in eucalyptus cuttings. The average cutting productivity on flat terrain was about 11 m3/E0h higher than on sloping terrain, mainly due to the time spent attaching the winch assistance system, which was a necessary phase of the work in sloping terrain. The research results suggest that it would be the most productive to use sideways felling inside the harvesting front method. However, the need for further research is evident if we want to precisely identify the harvesting conditions and work phases in the tree cutting cycle affecting the differences in the productivity of the harvesting chain in tree plantations.

Addressing non-unions involves stabilizing the affected area through osteosynthesis and improving bone biology using bone grafts. However, there is no consensus on the optimal treatment method. This study aims to compare outcomes of non-union revision using conventional treatment methods (metal hardware ± graft) versus osteosynthesis with the human, allogeneic cortical bone screw (Shark Screw®). Thirty-four patients underwent conventional treatment, while 28 cases received Shark Screws®. Patient demographics, bone healing, time to bone healing, and complications were assessed. Results revealed a healing rate of 96.4% for the Shark Screw® group, compared to 82.3% for the conventionally treated group. The Shark Screw® group exhibited a tendency for faster bone healing (9.4±3.2 vs. 12.9±8.5 weeks, p=0.05061). Hardware irritations led to six metal removals in the conventional group versus two in the Shark Screw® group. The Shark Screw® emerges as a promising option for personalized non-union treatment in the foot, ankle, and select lower leg cases, facilitating effective osteosynthesis and grafting within a single construct, promoting high union rates, low complications, and a rapid healing process.

The Brain-Computer Interface (BCI) technology has emerged as a groundbreaking innovation with profound implications across diverse domains, particularly in healthcare. By establishing a direct communication pathway between the human brain and external devices, BCI systems offer unprecedented opportunities for diagnosis, treatment, and rehabilitation, thereby reshaping the landscape of medical practice. However, despite its immense potential, the widespread adoption of BCI technology in clinical settings faces several challenges. These include the need for robust signal acquisition and processing techniques, ensuring user safety and privacy, addressing ethical considerations, and optimizing user training and adaptation. Overcoming these challenges is crucial to unleashing the complete potential of BCI technology in healthcare and realizing its promise of personalized, patient-centric care. This review work underscores the transformative potential of BCI technology in revolutionizing medical practice. This paper offers a comprehensive analysis of medical-oriented BCI applications by exploring the various uses of BCI technology and its potential to transform patient care.

It has been shown that Human papillomavirus (HPV) infection is associated with several forms of cancer. Additionally, although there are more than 100 types of HPV, more than ten types of it, including types 16 and 18, are considered high-risk. The two proteins that make up the viral capsid of HPV 16 are L1, the major capsid protein, and L2, the minor capsid protein. FDA (The Food and Drug Administration) approved HPV vaccines mostly target L1 and L2 capsid proteins, which facilitate intracellular entry during infection. In this study, it was set out to analyze the creation of phylogenetic relations of L1 nucleic acid sequences of viral isolates. This study also analyzed sequences of three key elements within the amino acid sequences of HPV 16 L1: loops critical for structural stability, nuclear localization signal sequences, and residues implicated in viral attachment. As highlighted by the literature, these elements represent pivotal aspects of viral function. Furthermore, the report highlighted the particular inter-sequence variability within the HPV 16 L1 protein sequences. Overall analysis revealed clustering of sequences primarily due to geographical and characterized by more phylogenetic relatedness within location-specific clusters.

The human mandible's cancellous bone, which is characterized by its unique porosity and directional sensitivity to external forces, is crucial for sustaining biting stress. Traditional CAD models fail to fully represent bone's anisotropic structure and thus depend on simple isotropic assumptions. For our research, we use the latest versions of nTopology and Creo Parametric software to make biomimetic Voronoi lattice models that accurately reflect the complex geometry and mechanical properties of trabecular bone. The porosity of human cancellous bone is accurately modeled in this work using biomimetic Voronoi lattice models. The porosities range from 70% to 95%, which can be achieved by changing the pore sizes to 1.0 mm, 1.5 mm, 2.0 mm, and 2.5 mm. Finite element analysis (FEA) was used to examine the displacements, stresses, and strains acting on dental implants with a buttress thread, abutment, retaining screw, and biting load surface. The results show that the Voronoi model accurately depicts the complex anatomy of the trabecular bone in the human jaw, compared to standard solid block models. The ideal pore size for biomimetic Voronoi lattice trabecular bone models is 2 mm, taking into account both the von Mises stress distribution over the dental implant, screw retention, cortical bone, cancellous bone, and micromotions. This pore size displayed balanced performance by successfully matching natural bone's mechanical characteristics. Advanced finite element analysis (FEA) improves biomechanical understanding of how bones and implants interact by creating more accurate models of biological problems and dynamic loading situations. This makes biomechanical engineering better.

Apoptotic cells possess immunomodulatory effects that can be utilized to treat imbalanced immune conditions. Information on the preclinical safety of such treatment is sparse. In this study, the safety of apoptotic cells (Allocetra-OTS) was assessed in a GLP toxicological study on Sprague Dawley rats. Three doses of Allocetra-OTS or vehicle were administered intravenously (IV) for 3 consecutive days. Animals in the Main study were sacrificed on day 4, while animals from the Recovery groups were kept for 14 or 28 days. Allocetra-OTS was well tolerated, and no adverse effects were observed in body weight, clinical signs, food consumption or ophthalmologic observation. Thus, the No Observed Adverse Effect Level (NOAEL) dose was determined as the highest dose administered. An observed elevation in immune cells was suspected to be due to Allocetra-OTS; similarly to other clinical chemistry parameters, however, it was resolved in the Recovery phases. Splenomegaly and a dose-related Extramedullary Hematopoiesis (EMH) in the red pulp were observed, with no adverse events, and were considered to be a normal and expected reaction following IV administration of cell-based therapies. In conclusion, under the conditions of this study Allocetra-OTS was concluded to be safe, further supporting its potential candidacy for clinical studies

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), one of the components constituting jumps, through a biomechanical model-based approach enables analysis even in environments where force plates or machine learning training data cannot be utilized. In this study, rotational jump movements involving twists on land were measured using inertial measurement units (IMUs) and estimated GRFs and body loads using a 3D forward dynamics model. Our estimation method, based on forward dynamics and optimization calculations, generated and optimized body movements using cost functions defined by motion measurements and internal body loads. To reduce the influence of the dynamic acceleration in the optimization calculation, the 3D orientation using sensor fusion composed of acceleration and angular velocity data obtained from IMUs and an extended Kalman filter was estimated. As a result, by generating movements based on the cost function, it was possible to calculate biomechanically valid GRFs while following the measured movements even if not all joints are covered by IMUs. This estimation method allows for 3D motion analysis independent of measurement conditions or training data.

Silybin is a natural compound extensively studied for its hepatoprotective, neuroprotective and anti-cancer properties. Envisioning the enhancement of silybin potential by suitable modifications in its chemical structure, here, a series of new 7-O alkyl silybins derivatives were synthesized by Mitsunobu reaction starting from the silybins and tyrosol-based phenols, such as tyrosol (TYR, 3), 3-methoxytyrosol (MTYR, 4) and 3-hydroxytyrosol (HTYR, 5). This research sought to explore the antioxidant and anticancer properties of new eighteen derivatives and their mechanisms. In particular, the antioxidant properties of new derivatives outlined by DPPH assay, showed a very pronounced activity depending on the tyrosyl moiety (HTYR&gt;MTYR&gt;&gt;TYR). A significant contribution of the HTYR moiety was observed for silybins and 2,3-dehydro-silybin based derivatives. According to the very potent antioxidant activity, 2,3-dehydro-silybin derivatives 15ab, 15a and 15b exerted the most potent anticancer activity in human prostate cancer PC-3 cells. Furthermore, flow cytometric analysis for cell cycle and apoptosis revealed that 15ab, 15a and 15b induce strong G1 phase arrest and increase late apoptotic population in PC-3 cells. Additionally, western blotting for apoptotic marker cleaved caspase-3 confirmed apoptosis induction by these silybin derivatives in PC-3 cells. These findings hold significant importance in the investigation of anticancer properties of silybin derivatives and strongly encourage swift investigation in pre-clinical models and clinical trials.

This article discusses how, in today’s world of disruptive and dramatic social change (DSC), non-sports related coaching, which includes a wide range of services such as life coaching, career coaching, executive coaching, and team coaching, can inadvertently fuel undesirable social dynamics. There is little or no awareness of this risk among coaches and coachees. The global, fast-growing, multi-billion-dollar industry aimed at supporting people and organisations to perform better and increase wellbeing while managing and adapting to change has been developed with limited sociological input. The article is based on 15 years of social constructionist-informed reflective practice by a sociologist-turned-coach, and uses a multi-layered autoethnographic account to argue for a sociologically informed paradigm shift in coaching, as well as relevant sociological knowledge and social and human sciences research methodology in coaches’ education. It presents the rationale and key features of a new coaching approach that places DSC-relevant sociological concepts at the heart of the coaching process, helps people develop psycho-sociological awareness, and uses a learning-to-develop through research design. A new definition of coaching to address DSC is derived. Coaching practitioners will find DSC-relevant sociological concepts, critical reflections, coaching questions, and procedures to expand coaching effectiveness. Interdisciplinary research topics combining coaching sociology and coaching psychology are suggested.

While providing safe water for the rural poor is considered a basic human right, there are numerous issues associated with existing technologies with shortcomings. Performance issues have continued to fail to meet the needs of impoverished families due to issues including high cost, difficulties with performance, and continuing needs for maintenance. These issues have severely interfered the safe water accessibility. Key aspects of the Guelph Water Filter (GWF) system can avoid/minimize many of these issues. The GWF as described herein enables delivery of low cost, long-term performance at 3Log removal of E.coli and can deliver 1 to 3 L of treated water per hour. The GWF is simple to operate, has an ability to provide sufficient water for a family, maintains longevity of performance, is easy to maintain and has protection against breakage during the cleaning process, is repairable at village level, and operates using a sizable reservoir of water to supply raw water, meaning the technology does not need to be refilled frequently. Hence, the capability of the novel GWF technology is shown to bypass many of the troublesome features of alternative low-tech water treatment technologies. The potential for the GWF to function for 2 days continuously avoids the need for young girls to fetch raw water frequently during a day, thereby enabling them to attend school. Hence, the GWF enhances the potential to result in ‘safe water and full schools’, providing the opportunity for girls to receive education and capture socio-economic benefits for the community.

The use of new assistive technologies in general, and Socially Assistive Robots (SAR) in particular is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due to design processes that insufficiently take into account the needs, preferences and values of intended users. Other issues are related to the currently very limited amount of long-term evaluations, performed in real world settings, for SAR. This study presents the results of two regional projects that consider as a starting hypothesis that the assessment in controlled environments and/or with short exposures may not be enough in the design of a SAR deployed in a retirement home and the necessity of designing for and with users. Thus, the proposed methodology has focused in use cases definitions that follow a human-centred and participatory design approach. The main goals have been facilitating system acceptance and attachment by involving stakeholders in the robots design and evaluation, overcoming usage barriers and considering user’s needs integration. The implementation of the first use case deployed and the two-phase pilot test performed in the retirement home are presented. In particular, a detailed description of the interface re-design process based on improving a basic prototype with users’ feedback and recommendations is presented together with main results of a formal evaluation that has highlighted the impact of changes and improvements addressed in the first redesign loop of the system.

Climate change, recognized as a global crisis, is not only altering our environment but also significantly impacting human health. Particularly, its influence on non-communicable diseases (NCDs), a leading cause of global mortality, is becoming increasingly evident yet underexplored. This review aims to synthesize current research on the impact of climate change on NCDs, addressing a critical gap in our understanding of how environmental changes affect human health. We examine the complex interplay between climate change and NCDs, drawing insights from recent studies that highlight the adverse effects of climate variables on chronic diseases, such as cardiovascular and kidney diseases, and the role of food and nutrition security in this nexus. Furthermore, the review explores the disproportionate impact on vulnerable regions and populations, particularly in Pacific Island countries and territories, underscoring the urgent need for context-specific solutions and a cross-sectoral approach. By integrating findings from various disciplines, this review aims to inform policy and public health interventions, highlighting the necessity of collaborative efforts to mitigate the burgeoning burden of NCDs in a rapidly changing climate.

Mercury contamination in the Amazon is a significant public health concern arising from both natural sources and intensive mining activities in the region. This metal is used to separate Au from sediments, forming an amalgam that facilitates the extraction of precious metals. Accordingly, this study aimed to address the following question: What is the impact of mining on mercury contamination in the animal and human populations of the Amazon? The overall objective of this study was to conduct a systematic review of the existing literature to identify gaps in geographic coverage and assess the impact of Hg contamination on human and animal populations in the Amazon region. Our hypothesis was that higher mercury concentrations in tissue samples would be found closer to the mining areas. We employed the PECO and PRISMA-ScR protocols to collect articles published between 2017 and 2023, selected based on criteria representing projected points on a map within the biogeographic boundaries of the Amazon. Mercury concentrations increase with trophic levels, reaching high values of 3.7 µg/g in the muscles of predatory fish and 34.9 µg/g in human hair. The average level of mercury in humans exceeds 6 µg/g, surpassing tolerance levels. Although mining regions show high concentrations of Hg, the highest incidence was observed among populations with fish-based diets. Research on fish is crucial for assessing the risk to human health, given that fish are the main source of protein in the region.

In contemporary construction, the prevalence of vibration serviceability issues in lightweight and slender structures has become increasingly common, owing to advancements in building materials and construction methods. While these structures often meet the criteria for ultimate limit states, they can still elicit complaints due to excessive vibrations induced by human activity. To address this challenge, the Integral Resonant Control (IRC) technique has emerged as a favored approach for actively damping vibrations in various systems. This study introduces a fresh perspective on implementing a multi-input multi-output (MIMO) IRC scheme for active vibration control (AVC) specifically tailored for pedestrian structures utilizing inertial mass actuators. Building upon a common framework and design methodology outlined in previous research, this work presents a novel application of MIMO IRC for AVC. The designed controller is rigorously tested and implemented on a laboratory floor structure to validate its efficacy.

: Julia Creek dunnarts are an endangered species of carnivorous marsupials and the focus of multiple conservation strategies involving significant resources such as captive breeding programs. Despite the relevance for conservation, no study to date has focused on evaluating geriatric diseases in dunnarts. This study describes the pathology findings in a group of one wild and 35 captive-born, mostly geriatric Julia Creek dunnarts that failed to produce offspring over multiple breeding periods. A total of 20 females and 16 males were submitted for a postmortem examination, with ages ranging from 9-42 and 12-42 months for females and males, respectively. Of these, 10 had unremarkable findings. The most common condition in females was cystic glandular hyperplasia (n=8), typical of hormonal dysregulation profiles in senescence, particularly hyperestrogenism. Rarely, cutaneous disease represented by unidentified dermal round cell infiltrates was observed in females (n=2). Primary reproductive hormonal dysregulation was also suspected in males diagnosed with testicular degeneration, aspermatogenesis and/or atrophy (n=3). Cutaneous round cell infiltrates, possibly compatible with epitheliotropic lymphomas were seen in males (n=3), and 2/3 affected males also had concurrent testicular degeneration or atrophy, indicating male sex could be a predictor for lymphoid neoplasia in aged dunnarts especially in individuals with concurrent testosterone-luteinizing hormone dysregulation as it occurs in gonadectomized animals. The role of an underlying viral etiology is also explored. This study is the first to describe major spontaneous diseases in endangered aged Julia Creek dunnarts, providing an important understanding of senescence and geriatric diseases within a conservation context.

In this study, the effect of NaOCl (10–200 ppm of Cl2) on the inactivation of human norovirus (HuNV) GII.4 and hepatitis A virus (HAV) in groundwater was investigated using PMA/RT­qPCR. Initially, 4.00 log copies/μL of HuNV GII.4 or 5.50 log copies/μL of HAV were artificially inoculated in ground water. The titers of HuNV GII.4 and HAV decreased significantly (p < 0.05) with increasing Cl2 concentrations. Ground water was treated with 10, 30, 50, 100, 150, and 200 ppm of Cl2, and the viable HuNV GII.4 was significantly (p < 0.05) reduced to 3.28 (0.21 log reduction), 3.18 (0.31 log reduction), 3.01 (0.48 log reduction), 2.75 (0.74 log reduction), 2.54 (0.95 log reduction), and 2.34 (1.15 log reduction) log copies/μL, respectively. The viable HAV was also significantly (p < 0.05) reduced to 4.99 (0.23 log reduction), 4.76 (0.46 log reduction), 4.55 (0.67 log reduction), 4.21 (1.01 log reduction), 3.89 (1.33 log reduction), and 3.64 (1.58 log reduction) log copies/μL, respectively. The decimal reduction time (D-value) (1-log reduction) of HuNV GII.4 and HAV infectivity in ground water was predicted as 116.7 and 98.9 ppm of Cl2, respectively using the first-order kinetics model (HuNV GII.4 ; y = - 0.0054x + 3.3585, R2= 0.97, HAV ; y = - 0.0091x + 5.0470, R2= 0.97). The result specifically suggests that 150–200 ppm Cl2 can potentially be used for the inactivation of > 1 log copies/μL HuNV GII.4 and HAV in ground water.

Herbal Coffee is getting more popular due to its unique flavor and higher concentration of bioactive compounds, mainly polyphenols. Rosemary is a unique herb with potent antioxidant properties. A green technique called ultrasound aids in releasing bioactive substances from the plant cell wall. In this context, ultrasound-assisted herbal coffee prepared and their anti-diabetic, anti-Alzheimer, and antioxidant activities were measured while the LC/MS was used to determine the bioactive components from the herbal coffee infusion. A total of 95 secondary metabolites were putatively reported, including alkaloids, phenolic acids, and flavonoids, which we identified in the herbal coffee infusion. The total phenolic content (61.5 ± 5.1 mg GAE/g), total flavonoid content (19.3 ± 0.9 mg QE/g), and total condensed tannin (7.6 ± 0.7 mg CE/g) of herbal coffee infusion were observed to be highest of the two remaining samples. The herbal coffee extracts were used to determine all samples' antioxidant, anti-diabetic, and anti-Alzheimer activities. Using LC-MS/MS, we semi-quantified 19 phenolic metabolites. The results show numerous bioactive components in herbal coffee infusion with more potent antioxidant, antidiabetic, and anti-Alzheimer potential. Moreover, more studies must be conducted to confirm how the metabolomic profile of herbal coffee affects its flavor profile.

Keywords: Marine Coasts; Protected Areas; Defense and Conservation; Asbestos Cement Materials; Wastes; Contamination; Human Health Risk; Medical Geology.

The water resources policy under climate change impacts water security, which should ensure enough water of good quality for humans and nature. Integrated water management is the state-of-the-art policy support model that, after 20 years in use, failed to achieve in many countries its primary goal of water bodies' good ecological status. Here, we show that this is due to the substantial externalities the anthropocentric character of the model generates. From the historical analysis, three main results are obtained: 1) the nature-human interplay is always composed of the coexistence of two opposite behaviors of conflict and cooperation; 2) this contradiction is a dialectical, general ontological attribute; 3) on the balance of power between nature and humans, three clusters are identified: i) naturalistic; ii) dualistic; iii) anthropocentric. A novel behaviorist dialectical conflict resolution model can resolve the differences between stakeholders and natural laws. The harmonic symbiosis of humans with nature removes environmental externalities and can lead to sustainable water security. Three case studies from the literature illustrate the merits of the new dialectical model.

Human action recognition (HAR) based on skeleton data is a challenging yet important technique because of its wide range of applications in many fields, including patient monitoring, security surveillance, and observing human-machine interactions. Many algorithms that attempt to distinguish between many types of activities have been proposed. However, most practical applications require highly accurate detection of specific types of activities. In this study, a novel and highly accurate spatiotemporal graph autoencoder network for HAR based on skeleton data is proposed. Furthermore, an extensive study was conducted using different modalities. For this purpose, a spatiotemporal graph autoencoder that automatically learns spatial as well as temporal patterns from human skeleton datasets was built. The powerful graph convolutional network named GA-GCN, developed in this study, notably outperforms most of the existing state-of-the-art methods based on two common datasets, namely NTU RGB+D and NTU RGB+D 120 . On the first dataset, we achieved an accuracy of 92.3% and 96.7% based on the cross-subject and cross-view evaluations, respectively. On the other more challenging dataset (i.e. NTU RGB+D 120), GA-GCN achieved 88.8% and 90.4% based on the cross-subject and cross-set evaluation, respectively.

This study examines the dynamic relationship between Green Human Resource Management (Green HRM), Environmental Performance (EP), Green Employee Behavior (GEB), and Environmental Knowledge and Awareness (EKAW) within the Egyptian hospitality sector context. Using Pearson correlation coefficients and regression analyses on a sample of 400 staff members from hotels and tourist villages in Egypt, the study examines Green HRM practices’ influence on EP, mediated by GEB and moderated by EKAW. The findings reveal significant positive correlations between Green HRM practices and these mediators, indicating that comprehensive environmental strategies and incentive management are pivotal in promoting eco-friendly practices among employees. The study further confirms GEB and EKAW’s substantial mediating role in enhancing EP. The results also suggest that while EKAW and GEB independently contribute to EP, their interaction and the role of environmental awareness as a potential moderator warrant further examination. This research contributes to the literature on sustainable business practices by underscoring human resource strategies’ integral role in achieving environmental sustainability goals, highlighting the importance of incentivizing green practices, and cultivating an organizational culture that prioritizes EKAW. These insights are particularly valuable for organizations seeking to enhance their ecological footprint through effective Green HRM practices.

Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tubes signals would serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method are presented.

Layered halide perovskites have emerged as a promising contender in solid-state lighting thanks to their tunable bandgap, high luminescence quantum yield, and high color purity. However, the fabrication of perovskite light-emitting devices in laboratories usually experiences low de-vice-to-device reproducibility since perovskite crystallization is highly sensitive to ambient condi-tions, such as humidity and temperature. Although device processing inside gloveboxes is primarily used to reduce the influence of oxygen and moisture, several extraneous variables, including gas-eous pollution traces and thermal fluctuations in the inert atmosphere or contaminations from re-sidual solvents confined in the enclosed environment, can destabilize the crystallization process and alter the properties of the emissive layers. Here, we examine different experimental set-ups for spin-coating deposition of layered perovskites in inert atmospheres and their influences on the formation of polycrystalline thin films. Our results demonstrate that fluctuations in the glovebox properties (concentrations of residual O2 and H2O or solvent traces), even in very short timescales, can negatively impact the consistency of the perovskite film formation, while thermal variation plays a relatively minor role in this phenomenon. Furthermore, careful storage of chemical species inside the workstation is critical for reproducing high-quality perovskite layers. Consequently, when applying our most controlled environment for perovskite deposition, the photoluminescence life-time of perovskite thin films shows a standard deviation of only 3%, whereas the reference set-up yields a 15% standard deviation. Regarding complete perovskite light-emitting diodes, the uncer-tainties in statistical luminance and EQE data are significantly reduced from 230% and 140% to 38% and 42%, respectively.

Introduction: The trophoblast derived angiogenic factors are considered to play an important role in the pathophysiology of various complications of pregnancy. The aim of this study was to establish relationship between concentrations of soluble Human Leukocyte Antigen-G (sHLA-G) in maternal serum and amniotic fluid at 16-22 weeks of gestation and the sonographic measurements of the fetal and placental growth. Materials and methods: sHLA-G in serum and amniotic fluid, as well as fetal biometric data and placental volume and perfusion indices were determined in 41 uncomplicated singleton pregnancies. Results: The sHLA-G levels were unchanged both in amniotic fluid and in serum during mid-pregnancy. The sHLA-G level in serum correlated positively with amniotic sHLA-G level (β=0.63, p<0.01). Significant correlation was found between serum sHLA-G level and abdominal measurement (β=0.41, p<0.05) and estimated fetal weight (β=0.41, p<0.05). The amniotic sHLA-G level and placental perfusion (VI: β = -0.34, p<0.01 and VFI: β = -0.44, p<0.01, respectively) were negatively interrelated. A low amniotic sHLA-G level was significantly associated with nuchal translucency (r = -0.102, p<0.05). Conclusions: sHLA-G assayed in amniotic fluid might be a potential indicator for placental function, whereas the sHLA-G level in serum can be a prognostic modality for feto-placental insufficiency.

Human endogenous retroviruses (HERV) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV promoting pathological conditions including the development of autoimmunity, neurodegenerative disease and cancer. What infections then trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases Crohn’s, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis and autoimmune thyroiditis. MAP is also associated with Parkinson’s disease. Autoimmune diabetes, multiple sclerosis and rheumatoid arthritis are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via unsilencing of HERV. We examine the link between the ever-increasing number of MAP- associated diseases, the MAP/HERV intersection with these diverse medical conditions and propose treatment opportunities based upon this association.

We develop new theory from a broad case-study approach to explore a better understanding of what constitutes knowledge and its value as identifiable to human-machine teams. From past research, this trail of exploration will lead to these initial questions: What is the value of debate in the furtherance of knowledge? Will machines with AI be able to contribute to a debate if we humans cannot define it or determine its value sufficiently for a machine’s understanding, contribution, exploration and identification? Like humans, as teammates, machines must be able to determine with AI what constitutes the usable knowledge that contributes to a team’s success in the field (e.g., testing "knowledge" in the field, identifying new knowledge, using knowledge to develop innovation) or its failure (viz., trouble shooting; identifying weaknesses; discovering vulnerabilities, hiding by deception). It matters not whether a debate is public, private or unexpressed by an individual human or machine agent alone; we speculate in this exploration that the process advances the science of autonomous human-machine teams and assists in interpretable machine learning. We conclude with questions and a speculation: How does a human become aware or express its awareness of knowledge? Can a machine be as expressive as its human teammates? And how does a human-machine teammate become aware that its teammates possess sufficient knowledge to perform a task? We speculate that the structure of “knowledge," once found, is resistant to alternatives (i.e., it is ordered); that its functional utility is generalizable; and that its applications are multifaceted (akin to maximum entropy production). The complexity of the team is taken into consideration in our search for knowledge, which can also be used as an information metric.

Collaborative robotics is a major topic in current robotics research posing new challenges, especially in Human-Robot Interaction. The crucial aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality will also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality and human factors will be explored, as this last aspect is vital to ensure safe and effective Human-Robot Interactions.

Iron deficiency in the fetal and neonatal period (perinatal iron deficiency) bodes poorly to neuro-development. Given its common occurrence and the negative impact on brain development, a screening and treatment strategy that is focused on optimizing brain development in perinatal iron deficiency is necessary. Pediatric societies currently recommend a universal iron supple-mentation strategy for full-term and preterm infants that does not consider individual variation in the body iron status and could lead to under-treatment or over-treatment. Moreover, the focus is on hematological normalcy and not optimal brain development. Several serum iron indices and hematological parameters in the perinatal period are associated with risk of abnormal neurodevelopment, suggesting their potential use as biomarkers for screening and monitoring treatment in infants at risk for perinatal iron deficiency. A biomarker-based screening and treatment strategy that is focused on optimizing brain development will likely improve outcome in perinatal iron deficiency.

This conceptual paper explores the potential of integrating Electromagnetic Fields (EMF) with traditional physiological signals to enhance emotional contagion in Human-Robot Interaction (HRI). A focused literature review identifies gaps in current HRI models that rely solely on visual, auditory, and known physiological cues for emotional exchange. A novel framework is proposed, incorporating EMF as a complementary modality, aiming to deepen emotional synchronization between humans and robots. The paper lays groundwork for future research to consider EMF detection as a complementary modality alongside traditional cues. It also addresses technological requirements and discusses potential limitations. By extending the modalities used in emotional contagion, this work seeks to advance the development of more intuitive and empathetic robotic systems.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

To better understand anogenital warts (AGW) natural history and dynamic of HPV6/11 infection in regional hairs, 32 newly diagnosed AGW male patients and 32 age-matched healthy controls were closely followed. During enrollment and six follow-up visits (every 2.6 months) 43 AGW tissue and 1,232 anogenital and eyebrow hair samples were collected. This represents the closest longitudinal monitoring of AGW patients to date. Patients were treated according to standard-of-care. HPV6/11 prevalence was 19.9% in patients’ hair samples (HPV6 B1 in 87.5%) and 0% in controls. The highest HPV6/11 prevalence was found in pubic hairs (29.0%) and lowest in eyebrows (7.1%). Odds for HPV6/11-positive hairs increased with smoking, shaving anogenital region and age. A close association between HPV6/11 presence in hairs and clinically visible AGW was observed. The proportion of patients with visible AGW and HPV6/11-positive hairs declined during follow-up with similar trends. No particular HPV6/11 variant was linked with increased AGW recurrence, but sublineage HPV6 B1 showed significantly higher clearance from hairs. Despite treatment, 78.1% and 62.5% of AGW patients experienced one and two/more post-initial AGW episodes, respectively. Patients having HPV6/11-positive hairs or visible AGW at preceding visit demonstrated substantially higher odds for presenting with visible AGW in subsequent visit.

Speech recognition, or automatic speech recognition (ASR), is a technology designed to convert spoken language into text using software. However, conventional ASR methods involve several distinct components, including language, acoustic, and pronunciation models with dictionaries. This modular approach can be time-consuming and may influence performance. In this study, we propose a method that streamlines the speech recognition process by incorporating a unified recurrent neural network (RNN) architecture. Our architecture integrates a convolutional neural network (CNN) with an RNN and employs a connectionist temporal classification (CTC) loss function. Key experiments were carried out using a dataset comprising 576,656 valid sentences, using erosion techniques. Evaluation of the model performance, measured by the word error rate (WER) metric, demonstrated remarkable results, achieving a WER of 2%. This approach has significant implications for the realm of speech recognition, as it alleviates the need for labor-intensive dictionary creation, enhancing the efficiency and accuracy of ASR systems, and making them more applicable to real-world scenarios. For future enhancements, we recommend the inclusion of dialectal and spontaneous data in the dataset to broaden the model's adaptability. Additionally, fine-tuning the model for specific tasks can optimize its performance for targeted objectives or domains, further enhancing its effectiveness in those areas.

There are two generic approaches to curing any medical condition. The first treats every patient for all of the known possible causes that contribute to pathogenesis; the second individualizes potentially curative therapy by identifying in each separate patient only those components of pathogenesis that are actually operative, and treating those. This article adopts the second approach for formulating a cure of Alzheimer’s dementia (AD). Components of AD’s pathogenesis are, in alphabetical order: circadian rhythm disturbances, depression, diabetes and insulin resistance, dyslipidemia, hypertension, inflammation, metabolic syndrome, mitochondrial dysfunction, nutritional deficiencies, TGF-β deficiency, underweight, vascular abnormalities, and Wnt/β-catenin deficiency. For each component, data are described that show the degree by which its prevalence is more in the patients with mild cognitive impairment (MCI) who did not revert to having normal cognition than in those who did, because the former group is the pool of patients from among which future AD may develop. Addressing only those components that are present in a particular individual, is potentially a curative strategy. Published data indicate that curative therapy requires that the number of such components to address should be ≥3. Although structural brain changes cannot be directly addressed, the impaired neural tracts result from many of the reversible causal elements, so correcting them will benefit those tract

Speech recognition, also known as automatic speech recognition (ASR), is a technology that enables software to transcribe spoken language into text. However, existing Amharic ASR methods require multiple separate blocks, such as language, acoustic, and pronunciation models with dictionaries, which can be time-consuming and influence performance. This study proposes an approach that replaces much of the speech pipeline with a single recurrent neural network (RNN) architecture. Our proposed architecture is based on a hybrid approach that combines a convolutional neural network (CNN) with a recurrent neural network (RNN) and a connectionist temporal classification (CTC) loss function. We conducted several experiments with noisy audio data that contain 20,000 valid sentences. The model was evaluated using the word error rate (WER) metric, achieving impressive results of 7% WER on noisy data. This approach has significant implications for the field of speech recognition, as it reduces the human effort required to create dictionaries and improves the efficiency and accuracy of ASR systems, making them more practical for real-world applications.

This study investigates the potential of natural compounds against HIV-1 protease, a critical enzyme in the replication cycle of human immunodeficiency virus type 1 (HIV-1). HIV-1 protease is essential for cleaving large precursor proteins into smaller functional proteins necessary for viral maturation and infectivity. Protease inhibitors, specifically targeting HIV-1 protease, effectively suppress viral replication, aiding in the management of HIV infection. Using the SWISS DOCK Server, several natural compounds were investigated for their potential as inhibitors of HIV-1 protease. Docking results revealed that Amentoflavone showed excellent binding affinity with high Estimated ΔG values, suggesting its potential as an inhibitor of HIV-1 protease. Additionally, Amentoflavone exhibited similar promising results when tested against Roussarcoma virus protease. These findings indicate the potential of Amentoflavone as a natural compound against HIV and warrant further investigation into its therapeutic applications.

Large Language Models (LLMs) have proved significant proficiency when comes to code generation especially in Structured Query Language (SQL) for databases and recent successful Text-to-SQL method involves fine-tuning pre-trained LLMs for SQL generation tasks. Transforming natural language text into SQL queries, has been attempted to solve with various learning techniques including Few-shot learning[1], fine tuning. In this paper we propose Supervised fine-tuning (SFT) as a better alternative for learning technique for text-to-SQL generation task using Code-Llama that pushes state of art accuracy on spider test suite to 89.6% on dev set which represent first instance of surpassing the earlier best-in-class with 5.5% higher score and 86.8% of exact match accuracy on dev set. Furthermore, we demonstrate that properly prompted LLM along with SFT provides far fewer hallucinations and much more robust LLM that can be used as a general tool for any text-to-SQL generation use case.

This study delves into the realm of potential therapeutics for breast cancer by conducting a comprehensive docking simulation and virtual screening analysis using Autodock Vina Algorithm. The focus based on the human epidermal growth factor receptor 2 (HER2), a key protein associated with various cancers, particularly in the context of breast cancer.The results reveal compelling insights into the binding interactions of several natural compounds and drugs with HER2. Notably, Acebilustat, Bemcentinib, and Amentoflavone exhibit outstanding binding energies, averaging around -10 kcal/mol, suggesting strong and favorable interactions with the HER2 target.These encouraging findings not only emphasize the potential biological significance of these compounds but also hint at their potential usefulness in fighting breast cancer.Their promising binding affinities with HER2 position them as potential candidates for further investigation and development as therapeutic agents against breast cancer.

Ensuring access to water, sanitation, and hygiene (WASH) facilities, coupled with behavior change education in schools, is fundamental for fostering a conducive learning environment and promoting principles of inclusion, dignity, and equality. This study focuses on 12 primary schools in Anápolis, Brazil, encompassing 4,394 students and 248 teachers. WASH assessments were conducted through a questionnaire, observation of water and sanitation facilities and structures, and microbiological analysis. Over the period 2018 to 2020, the proportion of schools with safely managed drinking water surged from 42% to 92%. However, sanitation conditions in the schools were categorized as a basic level, with hygiene services rated as limited in 92% of the schools due to the absence of soap. While this study reveals that Anápolis schools generally align with WASH guidelines for basic/advanced drinking water services, there is a crucial need for enhancements in both hardware and software facilities to address sanitation and hygiene challenges.

Clusterin (CLU) protein is involved in various pathophysiological processes including carcinogenesis and tumor progression. In recent years, the role of the secretory isoform has been demonstrated in tumor cells, where it inhibits apoptosis and favors the acquisition of resistance to conventional treatments used to treat cancer. To determine the possible therapeutic potential of inhibiting this protein, numerous studies have been carried out in this field. In this paper, we show the existing knowledge on the inhibition of this protein in different types of cancer and discuss the importance it could have in the development of new therapies directed against this pathology.

Wastewater-Based Epidemiology (WBE) is currently used to monitor not only the spread of the pandemic virus SARS-CoV-2 but also for other viruses in endemic conditions, particularly in the absence of syndromic surveillance. Continuous monitoring of sewage requires high costs and significant time investment, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Italy, targeting Human Adenovirus (HAdV), Norovirus Genogroup II (NoVggII), Enterovirus (EV), and SARS-CoV-2. Samples collected at the entrance of treatment plants were concentrated using PEG/NaCl precipitation and viral nucleic acids were extracted and detected by real-time (RT-)qPCR. NoVggII resulted the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. SARS-CoV-2 results compared with data previously collected in the same study area (February 2021 to September 2021) revealed a shift from an epidemic to a pandemic status, likely due to the evolution of variants. In conclusion, WBE, using standardized methods and an efficient monitoring strategy, proves valuable for virus surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decision.

Human papillomavirus (HPV) infections, primarily transmitted through sexual contact, have been linked to various cancers, including cervical, penile, anal, oropharynx, breast, and prostate cancers. This study presents a unique case of concurrent high-risk HPV35, HPV45, and HPV59 infections in both prostate and bladder cancer tissues from a single patient, representing the first documented instance worldwide with identical HPV types detected in two adjacent organs of the same individual. Employing a multiplex-PCR approach, gel electrophoresis, and Sanger sequencing, we confirmed the presence of these high-risk HPV types. Additionally, Western blot analysis using an HPV E7 antibody demonstrated the active expression of HPV oncoproteins in both cancer types. This discovery underscores the potential for HPV intra-organ transmission and necessitates further exploration of alternative transmission routes. The implications of our results offer new insights into the complex dynamics of HPV transmission in cancer pathogenesis.

Autonomous driving navigation relies on diverse approaches, each with advantages and limitations depending on various factors. For HD maps, modular systems excel, while end-to-end methods dominate mapless scenarios. However, few leverage the strengths of both. This paper innovates by proposing a hybrid architecture that seamlessly integrates modular perception and control modules with data-driven path planning. This innovative design leverages the strengths of both approaches, enabling a clear understanding and debugging of individual components while simultaneously harnessing the learning power of end-to-end approaches. Our proposed architecture achieved 1st and 2nd place in the 2023 CARLA Autonomous Driving Challenge’s SENSORS and MAP tracks, respectively. These results demonstrate the architecture’s effectiveness in both map-based and mapless navigation.

Before the emergence of SARS-CoV-1, MERS-CoV, and most recently SARS-CoV-2, al-ready four other coronaviruses have been circulating in the human population. The alpha coronaviruses NL63 and 229E and the beta coronaviruses OC34 and HKU1. These circulating coronaviruses all cause mild respiratory illness during the winter seasons and most people are already infected in early life. Could antibodies and/or T cells, es-pecially against the beta coronaviruses have offered some form of protection against SARS-CoV-2? Related is the question whether survivors of SARS-CoV-1 or MERS-CoV would be relatively protected against SARS-CoV-2. More importantly, would humoral and cellular immunological memory, generated during the SARS-CoV-2 pandemic, ei-ther by infection or vaccination offer protection against future coronaviruses? Or rather than protection, could antibody dependent enhancement have taken place, a mecha-nism by which circulating corona antibodies enhance the severity of COVID-19? An-other related phenomenon, the original antigen sin, would also predict that the effec-tivity of the immune response to future coronaviruses would be impaired because of reactivation of memory against irrelevant epitopes. Current available evidence indicates that latter scenarios are highly unlikely and that especially cytotoxic memory T cells directed against conserved epitopes of human coronaviruses could at least offer partial protection against future coronaviruses.

Children with severe acute malnutrition (SAM) are at high risk of impaired development. Contributing causes include inadequate intake of specific nutrients such as polyunsaturated fatty acids (PUFA) and lack of adequate stimulation. We conducted a pilot study assessing developmental and nutritional changes in children with SAM provided with a modified ready-to-use therapeutic food and a context-specific psychosocial intervention in Mwanza, Tanzania. We recruited 82 children with SAM (6-36 months) and 88 sex- and age-matched non-malnourished children. We measured child development, using the Malawi Development Assessment Tool (MDAT), measures of family and maternal care for children, and whole blood PUFA levels. At baseline, the mean total MDAT z-score of children with SAM was lower than non-malnourished children; -2.37 (95% confidence interval: -2.92; -1.82) as was their total n-3 fatty acids, eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) levels. After 8 weeks’ intervention, MDAT z-scores improved in all domains, especially fine motor, among children with SAM. Total n-3, and EPA levels increased, total n-6 fatty acids decreased, and DHA remained unchanged. Family and maternal care also improved. The suggested benefits of the combined interventions on developmental and nutritional status of children with SAM will be tested in a future trial.

(1) Background/Objectives: Accurate determination of chronological age is crucial in legal dental identification. This study aimed to compare the effectiveness of different formulas in estimating the age of a Brazilian subpopulation by analyzing the pulp/tooth ratio of the maxillary canine and mandibular second premolar in panoramic and periapical radiographs. (2) Methods: The sample consisted of panoramic and periapical radiographs of 247 individuals. The file of each radiograph was opened in the Adobe Photoshop CS4® program to outline and obtain values in pixels for calculating the pulp/tooth ratio. Statistical analysis was conducted using the SPSS program, with a significance level set at 5%. (3) Results: The interclass correlation coefficient demonstrated excellent intra-observer agreement (0.990 – 0.999). The determination coefficients (R2) suggested that only 30-35% of the actual age results could be explained by the pulp/tooth ratio. Smallest differences were observed with Cameriere's formula for the mandibular second premolar on panoramic radiographs (+4.1 years). The greatest differences were found with the formulas for the mandibular second premolar in panoramic radiographs of the Korean (+12.5 years) and Portuguese (-12.1 years) populations. (4) Conclusions: The equations employed allowed for estimating the age of a Brazilian subpopulation and showed little agreement between the actual age and the estimated age.

Transformer models have emerged as frontrunners in the field of natural language processing, primarily due to their adept use of self-attention mechanisms to grasp the semantic linkages between words in sequences. Despite their strengths, these models often face challenges in single-task learning scenarios, particularly when it comes to delivering top-notch performance and crafting strong latent feature representations. This challenge is more pronounced in the context of smaller datasets and is particularly acute for under-resourced languages such as Arabic. In light of these challenges, this study introduces a novel methodology for text classification of Arabic texts. This method harnesses the newly developed Reverse Positional Encoding (RPE) technique. It adopts inductive-transfer learning (ITL) framework combined with a switching self-attention shared encoder, thereby increasing the model's adaptability and improving its sentence representation accuracy. The integration of Mixture of Experts (MoE) and Reverse Positional Encoding (RPE) techniques empowers the model to process longer sequences more effectively. This enhancement is notably beneficial for Arabic text classification, adeptly supporting both the intricate five-point and the simpler ternary classification tasks. The empirical evidence points to its outstanding performance, achieving accuracy rates of 87.20% for the HARD dataset, 72.17% for the BRAD dataset, and 86.89% for the LABR dataset, as evidenced by the assessments conducted on these datasets.

Breast cancer is a multifaceted disease that has many subcategories characterized by unique genetic features. This research focuses on two important subgroups, including ER+ and HER2-. We conducted an analysis of gene expression data obtained from reliable sources (Array Express: E-GEOD-52194, E-GEOD-75367, and E-GEOD-58135) in order to reveal the complex molecular details of these subtypes. The computational pipeline we used identified 396 genes that exhibited distinct patterns of gene expression in ER+ and HER2- breast cancers. The diagnostic and prognostic significance of these genes was evaluated using machine learning methods, namely SVM and decision tree models. Metrics like as accuracy, sensitivity, and specificity provide insights into their usefulness. Furthermore, the use of the STRING database for network analysis revealed significant signaling pathways and biological processes associated with the development of ER+ and HER2- breast cancer. The results of our research enhance our comprehension of these subcategories, which might possibly facilitate more accurate diagnoses and focused treatment interventions. To summarize, this work provides valuable information on the genetic foundations of ER+ and HER2- breast cancer, which has potential implications for enhancing patient treatment and outcomes.

This study explores the potential of natural compounds, including Daidzin, Luteolin, and Silibinin, as inhibitors of human monoamine oxidase B (MAO-B) for the treatment of Parkinson's disease. Docking simulations were performed using Autodock Vina with Pyrx program to evaluate the binding affinities of these compounds with MAO-B. Results indicate that Daidzin, Luteolin, and Silibinin exhibit promising binding affinities with MAO-B, with Daidzin demonstrating the highest affinity. Toxicity parameters were further predicted using the PkCSM Server, confirming the low toxicity of these compounds. Overall, the findings suggest that Daidzin, Luteolin, and Silibinin have the potential to be effective and safe treatments for Parkinson's disease through their inhibition of MAO-B. Further experimental validation is warranted to support their therapeutic efficacy in clinical settings.

Gallium oxide (Ga2O3) is an emerging wide bandgap semiconductor promising a wide range of important applications. However, mass production of high-quality crystalline Ga2O3 still suffers from limitations associated with poor reproducibility and low efficiency. Low-temperature grown amorphous Ga2O3 demonstrates comparable performance with its crystalline counterparts. Lanthanide Er3+-doped Ga2O3 (Ga2O3: Er) possesses great potential for developing light-emitting devices, photodetectors and optical waveguides. The host circumstance can exert a crystal field around the lanthanide dopants and strongly influence their photoluminescence properties. Here we present a systematical study of the impact of amorphous-to-crystalline transition on the upconversion photoluminescence in Ga2O3: Er thin films. Through controlling the growth temperature of Ga2O3: Er films, the upconversion luminescence of as-grown thin films are strongly enhanced over 100 times. Moreover, the variation of photoluminescence reflects the amorphous-to-crystalline transformation of the Ga2O3: Er thin films. These results will aid further design of favorable optoelectronic devices integrated with lanthanide-doped Ga2O3 thin films.

The capacitor-mismatch among diverse defects caused by the manufacturing process variations significantly affects the linearity of capacitor-array used to implement the capacitive digital-to-analog converter (CDAC) in the successive-approximation-register (SAR) analog-to-digital converter (ADC). Accordingly, the linearity of the SAR ADC is limited by that of capacitor-array, resulting in serious yield loss. This paper proposes an efficient foreground self-calibration technique to enhance the linearity of the SAR ADCs by mitigating the capacitor-mismatch based on the split ADC architecture along with variable capacitors. In this work, two ADC channels (i.e., ADC1 and ADC2) for the split ADC architecture include their capacitive DACs (CDACs) whose binary-weighted capacitor-arrays consist of variable capacitors. A charge-sharing SAR ADC is used for each ADC channel. In the normal operation mode, their digital outputs are averaged to be the final ADC output, as in a conventional split ADC. In the calibration mode, every single binary-weighted capacitor for the two ADCs is sequentially calibrated by making parallel or/and antiparallel connection among two or thee capacitors from the two channels. For instance, because the capacitors of the CDACs ideally exhibit the binary-weighted relation as Cn=2×Cn−1, variable capacitor Cn of ADC1 can be updated to be closest to the sum of Cn−1 of ADC1 and Cn−1 of ADC2 for the calibration. For the process, the two capacitor-arrays of the two ADCs can be reconfigured to be connected to each other, so that Cn of ADC1 can be connected with two of Cn−1 of ADC1 and ADC2 in antiparallel. The two voltages at the top and the bottom plates of the CDAC are compared by a comparator of ADC1, and the comparison results are used to update Cn. This process is iterated, until Cn is in agreement with the sum of two of Cn−1. Finally, all the capacitors can be calibrated in this way to have the binary-weighted relation. The simulation results based on the proposed work with a split SAR ADC model verified that the proposed technique can be practically used, by showing that the total-harmonic-distortion and the signal-to-noise-and-distortion ratio were enhanced by 21.8-dB and 6.4-dB, respectively.

This study examines the moderating effect of trained human capital on the associations of accounting information systems, generalized auditing software, and technology adoption with the performance of external auditors among Saudi listed companies. This study used a survey-based methodology. The final sample consisted of 136 responses with an 8% response rate. Using Smart-PL4 analysis, the results showed that there is a positive correlation between accounting information systems and external auditors. Conversely, a negative relationship between generalized auditing software and external auditors has been documented. In addition, this study reported a negative association between technology adoption and external auditors. However, the results highlight the positive relationship between trained human capital and external auditors. Overall, this study provides valuable insights for accounting and auditing policymakers on how external auditors’ performance is influenced by several factors in the Saudi audit market.

Before December 2020, Antarctica had remained free of Covid-19 cases. The main concern during the pandemic was the limited health facilities available at Antarctic stations to deal with the disease, as well as the potential impact of SARS-CoV-2 on Antarctic wildlife through reverse zoonosis. In December 2020, 60 cases emerged in Chilean Antarctic stations, disrupting the summer campaign with ongoing isolation needs. The SARS-CoV-2 RNA was detected in the wastewater of several scientific stations. In Antarctica, treated wastewater is discharged directly into the seawater. No studies currently address recovery of infectious virus particles from treated wastewater, but their presence raises the risk of infecting wildlife and initiating new replication cycles. This study highlights the initial virus detection in wastewater from Antarctic stations, identifying viral RNA via RT-qPCR targeting various genomic regions. The virus's RNA was found in effluent from two wastewater plants at Maxwell Bay and O’Higgins Station on King George Island and the Antarctic Peninsula, respectively. This study explores the potential for reverse zoonotic transmission of SARS-CoV-2 from humans to Antarctic wildlife due to the direct release of viral particles into seawater. The implications of such transmission underscore the need for continued vigilance and research.

AbstractThe emergence of AI-powered deepfakes, manipulatively realistic synthetic media, raises unprecedented challenges for human information processing and decision-making. This paper explores the cognitive and emotional consequences of exposure to deepfakes, delving into how these digitally fabricated experiences can reshape perception, trust, and social interactions. By reviewing existing research and outlining potential methodological approaches, this paper aims to establish a framework for investigating the multifaceted impact of deepfakes on the human brain.BackgroundThe digital age has ushered in an era of unprecedented information abundance and accessibility. Yet, this abundance breeds vulnerability, particularly with the emergence of AI-powered deepfakes. These hyper-realistic synthetic media creations present a potent threat to the fundamental trust and integrity of information sources. Deepfakes have infiltrated various domains, from entertainment and social media to politics and journalism, blurring the lines between truth and fabrication. Consequently, understanding the cognitive and emotional consequences of encountering deepfakes becomes crucial for navigating this increasingly deceptive landscape.ObjectivesThis research aims to: Investigate how exposure to deepfakes impacts various cognitive functions, including perception, attention, memory, and decision-making. Elucidate the emotional responses elicited by deepfakes and their underlying neural mechanisms. Evaluate the role of individual differences, such as susceptibility to deception and emotional sensitivity, in mediating the impact of deepfakes. Develop a comprehensive framework for understanding the multifaceted influence of deepfakes on the human brain. Results (anticipated)This research is expected to yield insights into: The specific cognitive and emotional processes altered by deepfakes, providing evidence for potential mechanisms of deception and manipulation. The neural circuitry involved in detecting and responding to deepfakes, leading to the development of more effective detection methods. The influence of individual differences (e.g., age, cognitive style) on susceptibility to deepfakes, informing targeted interventions and educational efforts.ConclusionBy deciphering the impact of deepfakes on the human brain, this research will offer valuable tools for mitigating the harmful consequences of misinformation and promoting responsible use of this powerful technology. Ultimately, understanding how deepfakes manipulate our cognitive and emotional landscape is not merely a scientific pursuit, but a critical step towards ensuring a future where truth prevails in the digital world.

Gene editing is now easy to make new disease models through in-vivo and in vitro tests. It can potentially be used to make animals with single-gene or multiple-gene changes. The mutant strains with changed germlines are no longer needed with in vivo gene editing, which uses the CRISPR-Cas9 system to target cells of interest in their normal tissues. Whereas, the AAVs and other viral vectors have made it possible to change cells selectively. Gene editing hade made it possible to use human induced pluripotent stem cells (iPSC) to model diseases that run in families. Researchers can compare and contrast the human genomes of many different ethnic and racial groups using this method. Scientists may be able to make a disease in a lab dish using iPSCs from a patient. Using CRISPR, iPSCs made from patient cells can be fixed if they have certain problems. This shows that gene therapy is possible and shows what happens when cells aren't working right. The fact that CRISPR-Cas9 can change the DNA by just one nucleotide has had a huge effect on biological studies. CRISPR is becoming more and more popular, which shows how useful, easy, and effective it is. With the broad use of CRISPR-based apps, the tool is now used for much more than just changing genes. This method can be used to screen the whole genome, control the translation of genes based on their sequence, and edit several genes at the same time. Scientists can now model diseases in different species and learn more about how genes work because of these advances. Genome-wide association studies and genome-editing tools like CRISPR are giving us a good look at the future of personalized medicine.

The aim of the study was to identify factors associated with non-adherence to tuberculosis (TB) preventive treatment among contacts with latent TB infection of new cases of pulmonary TB cases reported in Catalonia in 2019-2021. All contacts aged 18 years or older with a latent TB infection who received a TB preventive treatment were included in the study. The Chi square test and the odds ratios (OR) were used to assess the association between non-adherence to TB preventive treatment and the study variables, considering a p < 0.05 as statistically significant. Multiple logistic regression analysis was used to detect the in-dependent factors associated with TB preventive treatment non-adherence, considering a p < 0.05 as statistically significant. The percentage of non-adherence to TB preventive treatment found in this study was 23.7%. A multivariable logistic regression analysis determined that the following factors were significantly associated with TB preventive treatment non-adherence among adult contacts: “exposure at school or workplace” (aOR = 3.34), “exposure to an index case without laboratory confirmation of TB” (aOR = 2.07), “immigrant contact” (aOR = 1.81), “male gender” (aOR = 1.75) and “exposure duration <6 hours per week or sporadic exposure” (aOR = 1.60). By contrast, the factor “short-term TB preventive treatment regimen” (aOR = 0.38) was significantly associated with a lower treatment non-adherence. Adherence to TB preventive treatment should be improved among adult contacts of TB pulmonary cases with latent TB infection by recommending short-term treatment regimens and by developing health education activities, with a greater focus on contacts with factors associated with treatment non-adherence.

Because it can make exact double-strand breaks in DNA, CRISPR-Cas9 can help almost every species and type of cell. It is a powerful way to change the DNA code. CRISPR-Cas9 can be used for a lot more than just changing genes. We are close to being able to do high-throughput gene screening, epigenome editing, in-vivo cell tagging, and RNA change. With the help of CRISPR-Cas9, the function of genes can be studied better, and more realistic disease models can be made. The revolutionary new discipline of gene editing has the potential to profoundly impact healthcare and the life sciences. By simplifying the process of creating double-strand breaks in the DNA of almost any species or kind of cell, CRISPR-Cas9 has revolutionized gene editing. Numerous applications have been found for the CRISPR-Cas9 system. High-throughput gene screening, RNA modification, live-cell chromosome marking, and epigenome editing are all examples. CRISPR-Cas9 facilitates gene research, leading to the development of CRISPR-based disease models. CRISPR-Cas9-based methods of altering the genome will aid researchers in learning more about sickness and discovering better ways to cure it, despite the fact that there are still many questions and large difficulties to answer.

The paper proposes a methodological way to compensate the imbalance between energy generation and consumption using the battery block of electric vehicles as energy reservoir through the well-known Vehicle to Grid system (V2G). The method is based on a simulation process developed by the authors that take into consideration the daily fluctuations of energy consumption as well as the power level generated by an energy source, either conventional, renewable or hybrid. The study shows that for very large electric vehicle fleet the system renders non-viable, since the remaining energy in the battery block to let the electric vehicle usable for running during daytime avoids to compensating for the energy grid imbalance, only allowing to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. The method allows predicting the optimum size of electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance and size of the electric vehicle fleet.

The studies regarding macrophage lncRNAs described in this review can help provide valuable information for developing treatments for various pathological conditions involving macrophages. Over the past century, molecular biology's focus has transitioned from proteins to DNA, and now to RNA. Once considered merely a genetic information carrier, RNA is now recognized as both a vital element in early cellular life and a regulator in complex organisms. Long noncoding RNAs (lncRNAs), which are over 200 bases long but do not code for proteins, play roles in gene expression regulation and signal transduction by inducing epigenetic changes or interacting with various proteins and RNAs. These interactions exhibit a range of functions in various cell types including macrophages. Notably, some macrophage lncRNAs influence the activation of NF-κB, a crucial transcription factor governing immune and inflammatory responses. Macrophage NF-κB is instrumental in the progression of various pathological conditions including sepsis, atherosclerosis, cancer, autoimmune disorders, and hypersensitivity. It orchestrates gene expression related to immune responses, inflammation, cell survival, and proliferation. Consequently, its malfunction is a key contributor to the onset and development of these diseases. This review summarizes the role of lncRNAs that regulate NF-κB in macrophage activation and inflammation, especially focusing on their implications in human diseases and their potential as therapeutic targets

Amidst the rapid advancements in artificial intelligence (AI) applications, determining the alignment between AI evaluations and human judgment remains crucial, especially in sectors like finance, healthcare, and education. This study delves into a unique scenario—a teenage entrepreneur pitch competition, mirroring real-world challenges faced by these young innovators. The objective was to assess the congruence between evaluations by ChatGPT, an AI model, and human judges. The results indicate a remarkable alignment between AI and human evaluations across several criteria. The implications of this study are far-reaching, highlighting AI's potential in ensuring unbiased and reliable evaluations in pitch competitions and beyond. However, navigating the juncture of AI and human judgment mandates continued research and ethical considerations.

The 2022-2023 Mpox multi-country outbreak, identified in over 110 WHO Member States, revealed a predominant impact on cisgender men, particularly those engaging in sex with men, while less frequently affecting women. This disparity prompted a focused investigation into the gender-specific characteristics of Mpox infections, particularly among women, to address a notable knowledge gap. This review systematically gathers and analyzes scientific literature and case reports concerning Mpox infections in women, covering a broad geographical spectrum including regions such as Buenos Aires, Brazil, Northern California, Colombia, Nigeria, Europe, Vietnam, Spain, Switzerland, and the United States. The analysis delves into various aspects of Mpox in women, including clinical features, epidemiology, psychological impacts, preparedness strategies, and case studies, with particular attention to pregnant women and those with underlying health conditions. Empirical data from multiple studies underscore the unique epidemiological and clinical patterns of Mpox in women. In the United States, a small percentage of Mpox cases were reported among cisgender women, with a notable portion involving non-Hispanic Black or African American, non-Hispanic White, and Hispanic or Latino ethnicities. The primary transmission route was identified as sexual or close intimate contact, with the virus predominantly manifesting on the legs, arms, and genital areas. Further, a study in Spain highlighted significant disparities in diagnosis delays, transmission modes, and clinical manifestations between genders, indicating a different risk profile and disease progression in women. Additionally, a case from Vietnam linked to a new Mpox sublineage in women emphasizes the role of women in the transmission dynamics and the importance of genomic monitoring. This review emphasizes the necessity for inclusive surveillance and research to fully understand Mpox dynamics across diverse population groups, including women. Highlighting gender and sexual orientation in public health responses is crucial for an effective approach to managing the spread and impact of the disease. The findings advocate for a gender-diverse assessment in health services and further research to explore the nuances of Mpox transmission, behavior, and progression among different groups, thereby enhancing the global response to Mpox and similar public health challenges.

Purpose: The aim of the study is an approach to a nanocomposite with copper nanoparticles, constituting a bacteriostatic surface for maintaining the human lung cells' function. Methods: The polyelectrolyte layer coating with copper nanoparticles incorporated was designed. As a bacteriostatic factor, copper nanoparticles were applied as a colloidal solution of copper nanoparticles (ColloidCuNPs) and solution of copper nanoparticles (CuNPs). The influence of polyelectrolytes on selected Gram(+) and Gram(-) strains was examined. The function of the human adenocarcinoma A549 cell line of epithelial human lung cells cultured in the presence of nanocomposite layer coatings was analyzed, as well as their morphology using flow cytometry, fluorescence microscopy, and scanning electron microscopy. In addition, the material of layer coating was assessed using AFM and SEM-EDX characterization. Results: It was observed that polyelectrolytes polyethylenimine and poly-L-lysine do not induce proliferation of E.coli strain. On the other hand, it induces the proliferation of S. aureus strain. Due to CuNPs effectiveness against E.coli strain, CuNPs were selected for further research. The designed coatings at proper NPs share sustained the function of human lung cells cultured within 10 days of culture. The AFM and EDX characterization confirmed copper presence in the layer coating nanomaterial. The presence of CuNPs in polyethyleneimine-based nanocomposite deepens the bacteriostatic effect on E. coli compared with PEI alone. Meanwhile, incorporating CuNPs in PLL at share allowed A549 cell maintenance, did not exert a bacteriostatic influence on the examined strain.Conclusion: The platform based on polyelectrolytes incorporated with copper nanoparticles ensuring the growth and morphology of the human lung epithelial cells can be considered an element of the system components for medical devices for maintaining the human lung cells' function.

Background: The research is conducted against the backdrop of the rising incidence of diabetes and the demand for novel approaches to improve patient outcomes. With the goal of revolutionizing conventional methods and addressing the changing healthcare landscape, the study concentrated on the application of AI technology in diabetes treatment. Objective: Examining the various ways AI can be used in diabetes care and assessing how it can enhance automated screenings, tailored treatment recommendations, predictive modeling, and patient self-management were the main goals of the study. Result: The findings demonstrated how well AI works to anticipate a patient's unique reaction to a therapy, assist medical personnel in making decisions, and give patients more control over their own care. Artificial intelligence (AI)-powered solutions showed promise in improving real-time monitoring and encouraging patient adherence, supporting a comprehensive strategy for managing diabetes. Conclusion: The research indicates that artificial intelligence (AI) has great potential to change the way diabetes is treated. However, it also highlights the need for more research, ethical issues, and validation of AI. The results advocate for joint efforts to ensure responsible and patient-centered technology innovation in diabetes care and encourage the integration of AI with new technologies.

Humans have a unique cognitive ability known as relational abstraction, which allows us to identify logical rules and patterns beyond basic perceptual characteristics. This ability represents a key difference between how humans and other animals learn and interact with the world. With current large language models rivaling human intelligence in many regards, we investigated whether relational abstraction was an emergent chat completion capacity in various models. We find that despite their impressive language processing skills, all tested language models failed the relational match-to-sample (RMTS) test, a benchmark for assessing relational abstraction. These results challenge the assumption that advanced language skills inherently confer the capacity for complex relational reasoning. The paper highlights the need for a broader evaluation of AI cognitive abilities, emphasizing that language proficiency alone may not be indicative of certain higher-order cognitive processes thought to be supported by language.

This review article seeks to systematically identify appropriate ways to measure managerial skills. The systematic literature review was conducted according to the criteria in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guide, and the eligibility criteria were declared through the PICOS tool (population, interventions, comparators, outcomes and study); a tool based on 6,803 records identified bibliometrically in the Web of Science database. The literature review stages determined a reduced set of articles that presented valid and reliable measurement scales covering some determinant constructs on managerial skills for employability such as fundamental, emotional, managerial, leadership, decision-making, communication and teamwork skills.

Using the potent tools of information geometry (IG), the current research analyses the information geometrics of the five-dimensional HTBFC Manifold. By enabling a unique revolutionary analysis for the performance of Human-Trust Based Feedback Control (HTBFC), the integration of information geometry into HTBFC facilitates the relativistic analysis of the five-dimensional HTBFC manifold. Both the two- and three-dimensional manifold subcases are investigated. This work provides a ground-breaking approach to IG unification of Human- Machine Interactions (HMIs). Some potential applications of HTBFC to robotics are presented.Conclusions are provided, along with some emerging open problems and recommendations for future research.

Safety limits application has always been a traditional approach to ensure the safe operation of electro-mechanical systems within many industries including automated vehicles, robotics, aerospace, traditional automotive, railways, manufacturing, etc. In all of these applications, control and safety limits are usually hard-coded into the production firmware and are fixed throughout the entire product life cycle. Currently, due to the evolving needs of automated systems like automated vehicles and robots, this traditional approach does not address all the use cases and scenarios to ensure safe operation. Especially for data-driven machine learning applications that constantly evolve and learn over time, it is important to be able to adjust the safety limits application strategy to be more flexible and adaptable based on different Operational Design Domains (ODDs) and scenarios. Our ITSC conference paper ~\cite{4} introduced the concept of a new safety limits application strategy called the Dynamic Control Limits Application (DCLA) strategy that supports the flexible application of diverse limits profiles based on the parameters involved within the dynamic scenario at different layers of the Autonomy software stack.This paper extends the DCLA strategy to derive the complete methodology for safety limits application based on ODD elements, scenario identification and scenario classification using Decision Making Engines. It leverages the layered architecture introduced in the ITSC conference paper to implement the Decision Making (DM) algorithms. Another important extension is the use of cloud infrastructure that is based on the Vehicle-to-Infrastructure (V2I) technology to store the scenarios and the limits mapping to serve as a ground truth and/or a backup mechanism in case of errors or failures associated with the main Decision Making (DM) Engine. There is also a focus on providing a more comprehensive list of scenarios and a custom built experimental dataset to cover the maximum ODD elements, and multiple tables of safety limits to be chosen from, which eventually helps in creating different safety limits application profiles. These distinct safety limits application profiles are based on the scenario parameters that are perceived by the system upon which the Decision Making algorithms are applied or trained. This systematic approach can be used within the industry for any of the future automated vehicles and systems until Level 5 Autonomy.

This study presents a literature review focused on nonverbal communication in human-robot interaction (HRI) that involves service robots with social capabilities. We aim to list the types of robots used and nonverbal communication cues examined in the reviewed studies; and the main research objectives, participant characteristics, data collection methods, and primary findings of these studies. To achieve this, we conducted a literature review of 39 relevant open access academic papers published from 2006 to 2023 that examined the utilization of nonverbal cues by both humans and robots during HRI. The results suggest that enhancing the quality of communication between humans and service robots must be improved, while there are several aspects that require more thorough exploring, needed to strengthen robot self-efficacy, trust and trustworthiness in HRI or overcome cultural differences. The results emphasize the importance of nonverbal communication in shaping the dynamics of interactions between humans and service robots.

This research focuses on the computational design and analysis of various winglet Design types on a Boeing 737 aircraft. The idea is to compare the efficiencies of various winglet design types on a Boeing 737 aircraft half wing span and the picking out the best winglet design in respect to the pressure generated at the wing-tip and the lift-to-drag ratio of each winglet designs. The coefficient of lift-drag ratio in this research contribute to the reduction of fuel consumption

The pathophysiology of Nonketotic Hyperglycinemia (NKH), a rare neuro-metabolic disorder associated with severe brain malformations and life-threatening neurological manifestations, remains incompletely understood. Therefore, a valid human neuronal model is essential. We aimed to investigate the impact of GLDC gene variants, which cause NKH, on cellular fitness during the differentiation process of human induced pluripotent stem cells (iPSCs) into iPSC-derived astrocytes and to identify sustainable mechanisms capable of overcoming GLDC deficiency. We developed the GLDC27-FiPS4F-1 line and performed metabolomic, mRNA abundance and protein analyses. The study showed that although GLDC27-FiPS4F-1 maintained the parental genetic profile, it underwent a metabolic switch to an altered serine-glycine-one-carbon metabolism with a coordinated cell growth and cell cycle proliferation response. We then differentiated the iPSCs into neural progenitor cells (NPCs) and astrocyte-lineage cells. Analysis showed that GLDC-deficient NPCs had shifted towards a more heterogeneous astrocyte lineage with increased expression of the radial glial markers GFAP and GLAST and the neuronal markers MAP2 and NeuN. In addition, we detected changes in other genes related to serine and glycine metabolism and transport, all consistent with the need to maintain glycine at physiological levels. These findings improve our understanding of the pathology and offer new perspectives for therapeutic options.

The Kanchenjunga Conservation Area (KCA) is a high mountain protected area in eastern Nepal undergoing socio-economic and environmental changes that are unprecedented in the region’s history. In the following paper, we discuss recent changes involving new road construction, climate change, adventure tourism, and the wildlife/forest cover/medicinal plant sectors. Our assessments are based on the collective results of past and recent field research, remote sensing analysis, oral histories, and literature reviews. While similar changes are occurring in mountain protected areas (MPA) throughout Nepal, it is suggested that the KCA differs from other regions in that it still retains the option of conducting detailed feasibility, environmental, and impact assessments prior to the implementation of major change-associated projects, particularly the construction of roads. In turn, the KCA might avoid many of the environmental, social, and economic problems experienced elsewhere in Nepal, while enhancing its status, income-generating capacities, and sustainability as a global destination for adventure, nature, and cultural tourism.

The classification of tumors in subtypes, characterized by phenotypes determined by specific differentiation pathways, aids diagnosis and directs therapy towards targeted approaches. However, with the advent and explosion of next-generation sequencing, cancer phenotypes are turning out to be far more heterogenous than initially thought, and the classification is continually being updated to include more subtypes. Tumors are indeed highly dynamic and they can evolve and undergo various changes in their characteristics during disease progression. The picture becomes even more complex when tumor responds to a therapy. In all these cases, cancer cells acquire the ability to trans-differentiate, changing subtype, and adapt to changing microenvironments. These modifications affect the tumor's growth rate, invasiveness, response to treatment, and overall clinical behavior. Studying tumor subtype transitions is crucial for understanding tumor evolution, predicting disease outcomes, and developing personalized treatment strategies. We discuss this emerging hallmark of cancer and the molecular mechanisms involved at the crossroads between tumor cells and their microenvironment, focusing on four different human cancers in which tissue plasticity causes a subtype switch: breast cancer, prostate cancer, glioblastoma and pancreatic adenocarcinoma.

In our increasingly urbanized world, precise and up-to-date maps of human settlements are essential for sustainable urban development policies. The availability of open-access Sentinel-2 data from the Copernicus program presents an opportunity to create a comprehensive global map of human settlements, offering a detailed view of built areas on a large scale. This study estimates large-scale built-up fractions using encoder-decoder deep learning architectures like U-net, Res-U-net, and Attention-U-net in the large and complex urban area of Delhi, India. Openly available datasets like Open Street Map (OSM) and Microsoft building footprint datasets are used to derive built-up fractions at 10×10m resolution cells for over 34,000 km2. Our results show that Attention-U-net with the Huber loss function performs the best in different built-up densities (i.e., urban, semi-urban or rural) with an R2 score of 0.631, while Res-U-net and U-net obtained an R2 score of 0.623 and 0.612, respectively. The investigated networks significantly improve the accuracy over the latest Global Human Settlement Layer product (GHSL-S2), which uses a deep-CNN and reaches an R2 of 0.387 in our case study area. The result of this study yields a valuable spatial layer for examining the spatial distribution of human settlements across the entire spectrum from rural to urban areas.

Disulfiram (DSF), an anti-alcoholism medicine, exerts treatment effects in patients suffering from persistent Borreliosis and also exhibits anti-cancer effects by its copper chelating derivatives. Since chronic/persistent borreliosis is characterized by increased amounts of proinflammatory macrophages, this study investigated opsonin-independent phagocytosis, migration and surface marker expression of in vivo activated human monocyte-derived macrophages and dendritic cells with and without DSF treatment. Phagocytosis of non-opsonized Dynabeads® M-450 and migration of macrophages and dendritic cells were monitored using live cell analyzer Juli™ Br for 24h by imaging every 3.5 min. Results were analyzed by a newly developed software based on the differential phase contrast images of cells before and after ingestion of Dynabeads bearing an electron dense iron core. As a control, phagocytosis was also monitored by visual counting of ingested beads. DSF decreased the phagocytic capacities exhibited by global macrophages and dendritic cells. DSF also impaired the migration of human monocyte-derived macrophages and dendritic cells (hMDMD) and significantly reduced the expression densities of surface antigens CD45 and CD14. In cells consisting of anti-inflammatory M2 macrophages, DSF led to a remarkable cell death and also increased oxidative stress as determined by MitoSox staining. Mitochondrial oxidative stress was a prominent feature in M2 macrophages which were more sensitive to DSF-induced cytotoxicity.

Genotypic testing is often recommended to improve the management of patients infected with human immunodeficiency virus (HIV). To help combat this major pandemic, next-generation sequencing (NGS) techniques are widely used to analyse resistance to antiretroviral drugs. In this study, we used a Vela Sentosa kit, which is usually used for the Ion Torrent personal genome machine (PGM) platform, to sequence HIV using the Illumina Miseq platform. After RNA extraction and reverse transcriptase-polymerase chain reaction (RT-PCR), minor modifications were applied to the Vela Sentosa kit to adapt it to Illumina Miseq platform. Analysis of the results showed the same mutations present in the samples using both sequencing platforms. The total number of reads varied from 185,069 to 752,343 and from 642,162 to 2,074,028 in the Ion Torrent PGM platform and the Illumina Miseq platform, respectively. The average depth was 21955 and 46856 for Ion Torrent PGM and Illumina Miseq platforms, respectively. The cost of sequencing a run of eight samples was closely similar between the two platforms (about 1 790 United States dollars [USD] for Illumina Miseq and about 1833 USD for Ion Torrent PGM platform). We have shown for the first time that it is possible to adapt and use the Vela Sentosa kit for the Illumina Miseq platform to obtain high quality results with a similar cost.

Human Pose Estimation (HPE) is a technique in computer vision and AI for detecting and tracking human body parts and poses from images or videos. Widely used in augmented reality, animation, fitness applications, and surveillance, HPE methods using monocular cameras are highly versatile due to their applicability in standard video and CCTV footage. These methods have evolved from 2D to 3D pose estimation. However, current 3D HPE methods trained on laboratory-based motion capture data encounter challenges such as limited training data, depth perception ambiguity, left/right switching, and issues with occlusions when applied in real-world environments. This study compares two representative 3D HPE methods by assessing their strengths and weaknesses with real-world videos. Then, we propose data processing techniques to eliminate and correct anomalies like left/right inversion and false detections of joint positions in daily life motions. Finally, we obtain joint angle trajectories using an optimization method based on a 3D humanoid simulator, taking as input the joint coordinate data corrected by applying the proposed human joint data processing technique. The efficacy of the proposed 3D HPE method is verified by applying it to three-dimensional freehand gymnastics exercises and comparing the joint angle trajectories during the motion.

This article delves into the complex tension between national self-rule and international involvement, in the context of global politics, examining the inherent challenges of upholding both principles when confronted with human rights abuses and the pursuit of global peace. The introduction presents the fundamental dilemma: self-governance versus moral obligations. The problem statement calls for a nuanced approach to address the intricate complexities of sovereignty and intervention, acknowledging the potential misuse by oppressive regimes and the ongoing challenges of determining when and how intervention is warranted. The article advocates for a more responsible and effective approach to global conflicts and human rights violations, balancing national sovereignty with judicious intervention when required. The methodology employs both literature review and case analysis to construct a framework for objectively assessing when international intervention is justified in instances of human rights abuses. The conclusion stresses the criticality of objective intervention criteria, transcending cultural, political, and economic biases, and advocates for a globally accepted approach that celebrates diversity while promoting global stability.

In the follow-up of treated high-grade cervical intraepithelial neoplasia (HSIL/CIN) lesions, cer-vical cytology has a high false-negative rate, while high-risk human papillomavirus (HR-HPV) DNA testing showed high sensitivity and lower specificity. The detection of messenger RNA of the HR-HPV E6 and E7 oncoproteins (E6/E7 mRNA) seems to be an indicator of viral integration and it allows the identification of severe lesions. Our objective was to assess the clinical utility of E6/E7 mRNA determination in the follow-up of patients treated for HSIL/CIN. A retrospective obser-vational study including 407 patients treated for HSIL/CIN was performed. The recurrence rate and the validity of E6/E7 mRNA testing were evaluated. The recurrence rate of high-grade lesions was 1.7%. The sensitivity of the test was 88% in the first clinical revision and 100% in the second and third revisions. Specificity was 91% in the first revision, 92% in the second revision, and 85% in the third revision. The positive predictive value was 18% in the first medical revision, 10% in the second and 14% in the third. The negative predictive value was 100% in all follow-up visits. In conclusion, the E6/E7 mRNA test seems to be effective in ruling out recurrence after treatment for HSIL/CIN lesions.