The concept of intellectual capital is increasingly recognized as one of the most important strategic assets of organizations. The significance of intellectual resources, which are now critical for every business unit, is underlined in this paper. Thus, this research aims to identify the effectiveness of intellectual capital and its components on the organizational innovation at Sulaimani Polytechnic University in Sulaymaniyah Governorate, from the point of view of the faculty members (academic and administrative staff). The study developed both theoretical and empirical sections. The descriptive approach was used to determine the effectiveness of intellectual capital and the quantities of research methodologies was used to measure this effectiveness. The study aims at investigating the correlations and causal effect between intellectual capital and organizational innovation. Moreover, the study investigates the correlations and causal effect between human capital, structural capital and relational capital on radical and incremental innovation in the organization. To achieve this, the 392 total sample were collected and analyzed by SPSS 22 software. The findings provide evidence that intellectual capital and its components have a positive and statistically significant effect on the organizational innovation and its components.

In this review, our goal is to design and test quantum-like algorithms for Artificial Intelligence (AI) in open systems to structure a human-machine team to be able to reach its maximum performance. Unlike the laboratory, in open systems, teams face complexity, uncertainty and conflict. All task domains have complexity levels, some have low, and others high levels. Complexity in this new domain is affected by the environment and the task, which are both affected by uncertainty and conflict. We contrast the individual and interdependence approaches to teams. The traditional and individual approach focuses on building teams and systems by aggregating the best available information for individuals, their thoughts, behaviors and skills. Its concepts are characterized chiefly by one-to-one relations between mind and body, a summation of disembodied individual mental and physical attributes, and degrees of freedom corresponding to the number of members in a team; however, this approach is characterized by the many researchers who have invested in it for almost a century with few effects that can be generalized to human-machine interactions; by the replication crisis of today (e.g., the invalid scales for self-esteem, implicit racism, and honesty); and by its many disembodied concepts. In contrast, our approach is based on the quantum-like nature of interdependence. It allows us to theorize about the bistability of mind and body, but it proposes a measurement problem and a non-factorable nature. Bistability addresses team structure and performance; the measurement problem solves the replication crisis; and the non-factorable aspect of teams reduces the degrees of freedom and the information derivable from teammates to match findings by the National Academies of Science. We begin with a review of the science of teams and a focus on human-machine team research in the laboratory versus the open; justifications for rejecting traditional social science while supporting our approach; a full understand of the complexity of the domain, tasks in the domain, and how teams address both; the mathematics involved; a review of results from our model versus the open field; a discussion of the results; conclusions; and the path forward to successfully advance the science of interdependence and autonomy.

Human pose estimation is a complex detection task in which the network needs to capture the rich information contained in the images. In this paper, we propose MSTPose (Multi-Scale Transformer for human Pose estimation). Specifically, MSTPose leverages a high-resolution Convolution neural network (CNN) to extract texture information from images. For the feature maps from three different scales produced by the backbone network, each branch performs the coordinate attention operations. The feature maps are then spatially and channel-wise flattened, combined with keypoint tokens generated through random initialization, and fed into a parallel Transformer structure to learn spatial dependencies between features. As the Transformer outputs one-dimensional sequential features, the mainstream two-dimensional heatmap method is abandoned in favor of one-dimensional coordinate vector regression. The experiments show that MSTPose outperforms other CNN-based pose estimation models and demonstrates clear advantages over CNN + Transformer networks of similar types.

Based on the eventual destruction of the solar system and the critical need for human continuation, this article suggests sending synthetic biology- and AI-created plant-like astronauts to the closest habitable exoplanet, Teegarden's Star b. Here we show that these astronauts will have green skin, blue blood, and the ability to perform photosynthesis. They could withstand cosmic radiation and extremely low temperatures in space while generating energy through photosynthesis. This groundbreaking interdisciplinary approach may provide a solution to the survival challenges faced by humans on their eternal interstellar journey. As long as plant-like astronauts possess human consciousness, it does not matter whether they are even a hybrid of carbon-based and silicon-based life. They will be a continuation of humanity on exoplanets. Human faces two options for survival. The first is the Mars migration program led by Elon Reeve Musk, which remains within the solar system and may not protect against the Sun's future scorching all life on the solar system during its red giant phase. The second option involves a more daring approach: the frantic escape of plant-like astronauts from the solar system. Should we consider both options simultaneously, much like how humans use their two legs to walk?

Fungi constitute a diverse group with highly positive and negative impacts in different envi-ronments, having several natural roles and beneficial applications in human life, but also caus-ing several concerns. Fungi can affect human health directly, but also indirectly by being detri-mental for animal and plant health influencing food safety and security. Climate changes are al-so affecting fungal distribution, prevalence, and their impact on different settings. Searching for sustainable solutions to deal with these issues is challenging due to the complexity of the inter-actions among fungi and agriculture, animal production, environment, and human health. In this way, the “One Health” approach may be useful to get some answers since it recognizes that human health is closely connected to animal and plant health, as well as to the shared environ-ment. This review aims to explore and correlate each of those factors influencing human health in this “One Health” perspective.

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded, respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.

The levels of informatization, automation, and intelligence are continuously improving; however, the risks due to the increased design and operational complexity of ship systems are increasing. Large-scale ship accidents occur for various reasons. Existing accident analysis methods that examine marine accidents from the perspective of causal one-to-one correspondence have limitations in systematically analyzing complex marine risks when identifying their causes for the prevention of similar accidents. This study focuses on a systematic causality analysis of the factors related to human errors in marine accidents that may occur during the arrival and departure of mega container ships. In particular, a representative case of the Milano Bridge crane contact accident at Busan New Port is considered. To explore the complex organizational–technical, human–technical, and organizational–human relationships relevant to this case, human factors (seafarer, pilot, etc) that are closely related to the linked causes were analyzed using the functional resonance analysis method. This study aims to reduce human error and prevent marine accidents including pilotage.

The German Constitutional Court’s climate verdict provides a re-interpretation of liberal- democratic core concepts and is highly relevant for liberal constitutional law in general – including EU and international law. The verdict accepts human rights as intertemporal and globally applicable; it applies the precautionary principle to these rights and frees them from the misleading causality debate. However, the court fails to address the most important violations of human rights, and it categorised climate policy as a greater threat to freedom than climate change. And the court does not make it clear that the Paris 1.5-degree limit implies a radically smaller carbon budget. Furthermore, little attention has so far been paid to the fact that the ruling implies an obligation for more EU climate protection, especially since most emissions are regulated supranationally. To be effective, the EU emissions trading system demands a reform, which should go well beyond the existing EU proposals to enable societal transformation to sustainability.

Human induced pluripotent stem cell (hiPSC)-derived neural cells have been used at the preclinical stage of drug development. As previously reported, hiPSC-derived neurons exhibit greater tolerance to excitotoxicity than that of primary cultures of rodent neurons; however, the underlying mechanisms remain unknown. We therefore investigated the functions of L-glutamate (L-Glu) transporters, the most important machinery used to maintain low extracellular L-Glu concentrations, in hiPSC-derived neural cells. We also clarified the contribution of each L-Glu transporter subtype. At 63 days in vitro (DIV), we detected neuronal circuit functions in hiPSC-derived neural cells by a microelectrode array system (MEA). Exposure to 100 μM L-Glu for 24 hrs did not affect the viability of these 63 DIV neural cells. Pharmacological inhibition of excitatory amino acid transporter 1 (EAAT1) and EAAT2 blocked almost 100% of L-Glu uptake. In this condition, L-Glu exposure dramatically decreased cell viability. These results suggest that in hiPSC-derived neural cells, EAAT1 and EAAT2 are predominant L-Glu transporters, and their uptake potentials are stronger than those of primary cultures of rodent neurons. Furthermore, hiPSC-derived neural cells may be useful for screening drugs that target L-Glu transporters.

There is little doubt that final victories over pandemics, such as COVID-19, are attributed to herd immunity, either through post-disease convalescence or active immunization of a high percentage of the world's population with vaccines, demonstrating protection from infection and transmission, being available in large quantities and at reasonable prices. However, it is assumable that humans with immune defects or immune suppression, e.g., as a consequence of allograft transplantation, cannot be immunized actively nor produce sufficient immune responses to prevent SARS-CoV-2 infections. These subjects desperately need other strategies, such as sophisticated protection measures and active immunization. Hypertonic salt solutions attack vulnerable core areas of viruses, i.e., salt denatures surface proteins and thus prohibits virus penetration of somatic cells. It has to be ensured that somatic proteins are not affected by denaturation regarding this unspecific virus protection. Impregnating filtering facepieces with hypertonic salt solutions is a straightforward way to inactivate viruses and other potential pathogens. As a result of the contact of salt crystals on the filtering facepiece, these pathogens become denatured and inactivated almost quantitatively. Such a strategy could be easily applied to fight against the COVID-19 pandemic and other ones that may occur in the future. Another possible tool to fight the COVID-19 pandemic is passive immunization with antibodies against SARS-CoV-2, preferably from human origin. Such antibodies can be harvested from patients´ human sera, which have successfully survived their SARS-CoV-2 infection. The disadvantage of a rapid decrease of the immunoglobulin titer after infection ends can be overcome by immortalizing antibody-producing B-cells via fusion with, e.g., mouse myeloma cells. The resulting monoclonal antibodies are then of human origin and available in, at least theoretically, unlimited amounts. Finally, dry blood spots are a valuable tool for surveilling the population´s immunity.

More than 1 million women are diagnosed annually worldwide with a gynecological cancer. Most gynecological cancers are diagnosed at late stage, either because lack of symptoms such as in ovarian cancer or limited accessibility to primary prevention in low-resource countries such as in cervical cancer. Here, we extend the studies of AR2011, a stroma-targeted and tumor microenvironment responsive oncolytic adenovirus (OAdV) whose replication is driven by a triple hybrid promoter. We show that AR2011 was able to replicate and lyse in vitro fresh explants obtained from human ovarian cancer. uterine cancer, and cervical cancer. AR2011 was also able to strongly inhibit the in vitro growth of ovarian malignant cells obtained from human ascites fluid. The virus could synergize in vitro with cisplatin even on ascites-derived cells obtained from patients heavily pretreated with neoadjuvant chemotherapy. AR2011(h404) a dual transcriptionally targeted derived virus armed with hCD40L and h41BBL under the regulation of the hTERT promoter, showed a strong efficacy in vivo both on subcutaneous and intraperitoneally established human ovarian cancer in nude mice. Preliminary studies in an immunocompetent murine tumor model showed that AR2011(m404) expressing the murine cytokines was able to induce an abscopal effect. The present studies suggest that AR2011(h404) is a likely candidate as a novel medicine for intraperitoneal disseminated ovarian cancer.

In recent years, bone tissue engineering (BTE) has made significant progress in promoting the direct and functional connection between bone and graft, including osseointegration and osteoconduction, to facilitate the healing of damaged bone tissues. Herein, we introduce a new, environmentally friendly, and cost-effective method for synthesizing reduced graphene oxide (rGO) and hydroxyapatite (HAp). The method uses epigallocatechin-3-O-gallate (EGCG) as a reducing agent to synthesize rGO (E-rGO), and HAp powder is obtained from Atlantic bluefin tuna (Thunnus thynnus). The physicochemical analysis indicated that the E-rGO/HAp composites had exceptional properties for use as BTE scaffolds, as well as high purity. Moreover, we discovered that E-rGO/HAp composites facilitated not only proliferation, but also early and late osteogenic differentiation of human mesenchymal stem cells (hMSCs). Our work suggests that E-rGO/HAp composites may play a significant role in promoting the spontaneous osteogenic differentiation of hMSCs, and we envision that the E-rGO/HAp composites could serve as promising candidates for BTE scaffolds, stem cell differentiation stimulators, and implantable device components due to their biocompatible and bioactive properties. Overall, we suggest a new approach for developing cost-effective and environmentally friendly E-rGO/HAp composite materials for BTE application.

The primary cilium plays critical roles in homeostasis and development of neurons. Recent studies demonstrate that cilia length is regulated by the metabolic state of cells, as dictated by processes such as glucose flux and O-GlcNAcylation (OGN). The study of cilia length regulation during neuron development, however, has been an area left largely unexplored. This project aims to elucidate the roles of O-GlcNAc in neuronal development through its regulation of the primary cilium. Here, we present findings suggesting that OGN levels negatively regulate cilia length on differentiated cortical neurons derived from human-induced pluripotent stem cells. In neurons, cilia length increased significantly during neurons maturation (after day 35), while OGN levels began to drop. Long-term perturbation of OGN via drugs, which inhibit or promote its cycling, during neuron development also have varying effects. Diminishing OGN levels increases cilia length until day 25, when neural stem cells expand and undergo early neurogenesis, before causing cell cycle exit defects and multinucleation. Elevating OGN levels induces greater primary cilia assembly but ultimately results in the development of premature neurons, which have higher insulin sensitivity. These results indicate that OGN levels and primary cilia length are jointly critical in proper neuron development and function. Understanding the interplays between these two nutrient sensors, O-GlcNAc and the primary cilium, during neuron development is important in paving connections between dysfunctional nutrient-sensing and early neurological disorders.

The impetus for the development of coaching as a professional managerial activity is based on the needs and requirements of a modern sustainable society. The paper aims to explore the awareness of academic students about the coaching approach and to formu-late recommendations for its application in the academic environment. The article focuses on the views of experts in the field of coaching approach as a means of improving com-munication in the academic/educational setting, characterizes communication and coaching approach, coaching models and its benefits and barriers. The survey presents a survey of awareness of the coaching approach among college and university students of in Slovakia and the possibilities/options of its application in the academic environment. The research was carried out by the questionnaire method. The evaluation of the questionnaire and the statistical evaluation of established hypotheses and assumptions concerning the coaching approach. The proposion of students was the introduction of the subject "Basics of coaching" which could be taught for all students at University of Zilina, Slovakia. Acording to the survey, 468 students, representing 68%, have knowledge about coaching. Furthermore, 68% of students had or have doubts about achieving their goals during their studies. According to the results of the survey, only 24% of students had ex-perience with coaching. The cooperation with a coach was regarded as beneficial for 71% of participants of the survey, which had already experience the coaching lectures. The students of managerial fields would benefit in enhancing leadership skills and providing support of their working teams.Finally, suggest organizing an introductory full-day workshops for students of man-agement -future managers, followed by organizing individual thematic workshops for specific areas of coaching.Moreover, the usage of coaching skills is possible yet while they are students with applications in communication in their relationships, student jobs, searching the profes-sional job opportunities and accomplishing the final thesis.To raise awareness of coaching approach in the University of Zilina in a cooperation with The Counseling and Career Center and its activities.

Human adenoviruses are one of the most important pathogens detected in acute respiratory diseases in pediatrics and immunocompromised patients. In 1953, Wallace Rowe described it for the first time in oropharyngeal lymphatic tissue. To date, more than 85 types of HAdV have been described, with different cellular tropisms. They can cause respiratory and gastrointestinal symptoms, even urinary tract inflammation, although most infections are asymptomatic. However, there is a population at risk that can develop serious and even lethal conditions. These viruses have a double-stranded DNA genome, 25-48 kbp, 90 nm in diameter, without a mantle, stable in the environment, and resistant to fat-soluble detergents. Currently the diagnosis is made with lateral flow immunochromatography or molecular biology through a polymerase chain reaction. The objective of this review is to recognize the variability of HAdV, the pandemic potential that a recombinant could present between HAdV-3 and 7 viral types, known to produce aggressive outbreaks in health facilities. The review determined the characteristics of HAdV, from the infection to treatment, vaccine development and the evaluation of the social determinants of health associated with HAdV, guiding the necessary measures for future sanitary control, and preventing disasters such as the SARS-CoV-2 pandemic.

Mangroves are among the world’s most threatened ecosystems. Understanding how these ecosystems responded to past natural and anthropogenic drivers of ecological change is essential not only for understanding how extant mangroves have been shaped, but also for informing their conservation. This paper reviews the available paleoecological evidence for Pleistocene and Holocene responses of Caribbean mangroves to climatic, eustatic and anthropogenic drivers. The first records date from the Last Interglacial when global average temperatures sea levels were slightly higher than the present and mangroves grew in locations and conditions similar to today. During the Last Glaciation temperatures and sea levels were significantly lower and Caribbean mangroves grew far from their present locations, on presently submerged sites. Current mangrove configuration was progressively attained after Early Holocene warming and sea-level rise, in the absence of anthropogenic pressure. Human influence began to be important in the Mid-Late Holocene, especially during the Archaic and Ceramic cultural periods, when sea levels were already at their present position, and climatic and human drivers were the most influencing factors. During the last millennium, the most relevant drivers of ecological change have been the episodic droughts linked to the Little Ice Age and the historical developments of the last centuries.

Objectives: Human herpes viruses can cause life-threatening diseases in immunocompromised children, especially leukemic patients. Therefore, the aim of this study is to detect the human herpes viruses (HHV1-7) and to investigate its clinical significance in Middle Eastern Pediatric Leukemia Patients by using 2 Independent PCR assays. Methods: Detection of human herpes virus DNA has been done in blood samples of 200 pediatric leukemia patients in addition to 90 blood donors as a control group using multiplex PCR assays. When a ‘‘positive’’ result was observed, real-time PCR was performed to measure the viral load. Results: The most frequent herpes virus infection in Middle Eastern Pediatric Leukemia cases was CMV, followed by EBV, then HHV6, VZV, HHV7, HSV1, and HSV2, where they were 92/200 (46%), 76/200 (38%), 72/200 (36%), 48/200 (24%), 12/200 (6%), 8/200 (4%), and 2/200 (1%) respectively. Also, there was a statistically significance difference between leukemic patients and their controls regarding CMV, EBV, HHV6, and VZV (P <0.05). Correlation between percentage of co-infection, and clinical parameters for the 7 herpes viruses has been studied, and there is an increase in absolute neutrophilic count (ANC), total leukocyte count (TLC) and duration of fever and neutropenia in age group 6-11 years for HHV6/CMV, then in age group 12-18 years especially for EBV/CMV and CMV/HHV6. Also, our results show that multiplex PCR assay is close to single PCR assay in relation to specificity and sensitivity which in turn prove its validity for early diagnosis of herpes viral infection. Conclusions: Adopting multiplex PCR technique is helpful in screening of virus infections. It will save time, effort, cost effective and will assist in rapid diagnosis. However, the clinical relevance of the virus infection needs to be evaluated by quantitative real-time PCR which in turn will help patient's management by using appropriate antiviral treatment.

Although the fusion energy sector is at a nascent stage, the private fusion energy market has grown. There are currently 38 private fusion energy companies around the world aiming to commercialise fusion energy in early 2030s and 2040s. Given the capability of fusion energy in transforming today’s energy paradigm and the global character of the market, it is important to analyse how these companies are interacting with international human rights standards. Therefore, this work investigates the involvement of the private fusion energy sector with two voluntary international initiatives in particular: the UN Global Compact and the UN Guiding Principles on Business and Human Rights (UNGP). This study attempts to answer two research questions: (i) Are private fusion energy companies participating in the UN Global Compact? (ii) How are private fusion energy companies publicly implementing the UNGP? Content analysis of secondary data collected from the UN Global Compact, Fusion Industry Association, ITER and companies’ official website as well as published reports is adopted. In summary, this work finds that private fusion energy companies are neither participants nor signatories of the UN Global Compact. Their observance of the UNGP is also very poor. This study contributes to the field by highlighting this gap which the private fusion energy companies need to consider and take measures in order to create a salutary human rights sector.

Background: The course of obesity and type 2 diabetes (T2D) development is highly dependent on adipose tissue (AT) angiogenesis. Moreover, angiogenic microRNAs (miRNAs) play pivotal role in AT functionality. The aim of this study was to analyze the relationship of the human AT miR-221-3p/222-3p cluster and their regulatory network with obesity and T2D. Methods: miR-221-3p/222-3p and their target genes (TG) expression levels were measured in visceral and subcutaneous ATs from patients classified according to their BMI and to their glycemic status with a high degree of insulin resistance (IR) and T2D. In silico analyses of miR-221-3p/222-3p and their TGs were performed to identify relevant signaling pathways. Results: A multivariate analysis, including the simultaneous expression of miR-221-3p and miR-222-3p as dependent variables, showed significant differences considering the variables; tissue depot, obesity, IR and T2D altogether as independent variables. In addition, miRNAs and their TGs were differentially expressed according to obesity degree, glycemic status, and AT depot type. Our in silico analysis showed that miR-221-3p/222-3p cluster TGs are mostly involved in angiogenesis, WNT signaling pathway and apoptosis. Conclusion: These findings suggest that the miR-221-3p/222-3p cluster and their related regulatory networks could represent tangible targets for the management of obesity and associated metabolic disorders

Background: Intelligence quotient (IQ) is a measure of intellectual ability of performing, comprehension, and learning. Previous studies reported that intelligence measures predict various measures of job performance and income. Emotional awareness (EA) is the measure of emotional capacity to recognize and make sense of one’s emotions, as well as those of others. A high level of emotional awareness (EA) indicates one can learn from expressed emotions quickly. Both IQ and EA are important for personal and professional success.Objective: This study tests the hypothesis that the average national income rank is best predicted by the combined effect of the population's average intelligence quotient (one's ability to perform and learn) and emotional awareness (ability to recognize and make sense of emotions).Method: The population’s average intelligence quotient (IQ), emotional awareness (EA), and indices of good governance, which include corruption perception index and educational expenses for each country, were obtained from public data sources. The outcome variable was per capita gross national income. All the variables that are statistically significant in univariate analysis were included in the multivariate regression analyses but excluded from the final model if not statistically significant.Result: The total number of countries included in the final analysis was 81 because of missing values in different variables. Intelligence quotient (IQ) and emotional awareness (EA) were found to be highly correlated, at 0.77 and 0.32 respectively, with the per capita gross national income. The independent effects of intelligence quotient (IQ) and emotional awareness (EA) were found significant in the multivariate model after adjusting for measures of good governance. The R square value for the final multivariate model was 0.82. The corruption perception index (CPI) and educational expenses were strongly correlated with other measures of good governance such as democracy index, functioning of government, electoral process and pluralism, political participation, and civil liberty, but these variables were found not significant in the multivariate model. Conclusion: The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence. The study concludes the effect of intelligence quotient (IQ) and emotional awareness (EA) are complementary to each other but intelligence quotient (IQ) is a stronger predictor than emotional awareness (EA) for gross national income or wealth. We also find that indicators of good governance, including corruption perception index and educational expenses, have important associations with per capita gross national income. This study implies a nation may build more wealth if the educational system focuses on developing emotional awareness in addition to intelligence.

Tuberculosis (TB) remains a major public health threat globally, especially in sub-Saharan Africa. Both human and Mycobacterium tuberculosis (MTBC) genetic variation affect TB outcomes, but few studies have examined if and how the two genomes interact to affect disease. We hypothesize that long-term coexistence between human genomes and MTBC lineages modulate disease to affect its severity. We examined this hypothesis in our TB household contact study in Kampala, Uganda, in which we identified 3 MTBC lineages of which one, L4.6-Uganda, is clearly derived and hence recent. We quantified TB severity using the Bandim TBscore and examined the interaction between MTBC lineage and human single nucleotide polymorphisms (SNPs) genome-wide, in two independent cohorts of TB cases (N=149 and N=127). We found a significant interaction between a SNP in PPIAP2 and the Uganda lineage (combined p=4x10-8). PPIAP2 is a pseudogene that is highly expressed in immune cells. Pathway and eQTL analyses indicated potential roles between coevolving SNPs and cellular replication and metabolism as well as platelet aggregation and coagulation. This finding provides further evidence that host-pathogen interactions affect clinical presentation differently than host and pathogen genetic variation independently, and that human-MTBC coevolution is likely to explain patterns of disease severity.

Background and aims: Despite recent advances in advanced prostate cancer treatments, there are no clinically useful biomarkers or treatments for men with such cancers. Targeted therapies have shown promise, but there remain fewer actionable targets in prostate cancer than in other cancers. This work aims to characterize BRD9, currently understudied in prostate cancer, and investigate its co-expression with other genes to assess its potential as a biomarker and therapeutic target in human prostate cancer. Materials and methods: Omics data from a total of 2053 prostate cancer patients across 11 independent datasets were accessed via Cancertool and cBioPortal. mRNA expression and co-expression, mutations, amplifications, and deletions were assessed with respect to key clinical parameters including survival, Gleason grade, stage, progression and treatment. Network and pathway analysis was carried out using Genemania, and heatmaps were constructed using Morpheus. Results: BRD9 is overexpressed in prostate cancer patients, especially those with metastatic disease. BRD9 expression did not differ in patients treated with second generation antiandrogens versus those who were not. BRD9 is co-expressed with many genes in the SWI/SNF and BET complexes, as well as those in common signaling pathways in prostate cancer. Summary and conclusions: BRD9 has potential as a diagnostic and prognostic biomarker in prostate cancer. BRD9 also shows promise as a therapeutic target, particularly in advanced prostate cancer, and as a co-target alongside other genes in the SWI/SNF and BET complexes, and those in common prostate cancer signalling pathways. These promising results highlight the need for wider experimental inhibition and co-targeted inhibition of BRD9 in vitro and in vivo, to build on the limited inhibition data available.

Cyber defense is reactive and slow. On average, the time-to-remedy is hundreds of times larger than the time-to-compromise. In response to the expanding ever-more-complex threat landscape, Digital Twins (DTs) and particularly Human Digital Twins (HDTs) offer the capability of running massive simulations across multiple knowledge domains. Simulated results may offer insights into adversaries' behaviors and tactics, resulting in better proactive cyber-defense strategies. For the first time, this paper solidifies the vision of DTs and HDTs for cybersecurity via the Cybonto conceptual framework proposal. The paper also contributes the Cybonto ontology, formally documenting 108 constructs and thousands of cognitive-related paths based on 20 time-tested psychology theories. Finally, the paper applied 20 network centrality algorithms in analyzing the 108 constructs. The identified top 10 constructs call for extensions of current digital cognitive architectures in preparation for the DT future.

The demand for animal products is expected to continue to rise, which requires the development of efficient livestock farming systems. Environmental, societal and economic concerns regarding this industry are however accumulating, addressing the large resource demand, pollutants and greenhouse gas emissions and health concerns that the livestock industry is responsible for. Precision livestock farming systems allow the continuous automatic monitoring of various physiological, behavioural and phenotypic parameters of animals in order to increase productivity and animal welfare while controlling and minimizing the environmental impact. There is a high potential for digital farming to be the solution for responsibly and ethically feeding the growing and urbanizing population. However, many problems and concerns are still present in this developing industry and remain relatively unaddressed, starting with the ethical aspects in regard to the animal, including its objectification, human-animal relationships and welfare and ending with the societal implications of this digitalization. Concrete frameworks, inter-disciplinary studies and global legislation need to be put in place in order to ensure the safety and protection of the animals, farmer and society. Here, implications of digital farming for the animals, farmers, society and the planet are critically reviewed with the future outlook of digital farms.

Mechanical robustness, biocompatibility, and antibacterial performances are key features for materials suitable to be used in tissue engineering applications. In this work, we investigated the link existing between structural and functional properties of TiCu(Ag) thin films deposited by physical vapor deposition magnetron sputtering on Si substrates. The thin films were characterized by X-ray diffraction (XRD), nanoindentation, atomic force microscopy (AFM), and X-ray photoelectron spectroscopy (XPS). The TiCu(Ag) thin films showed complete amorphous structure and improved mechanical properties in comparison with pure Ti films. However, for contents in excess of 20% Ag, we observed the appearance of nanometric Ag crystallite. The TiCu(Ag) thin films displayed excellent biocompatibility properties, allowing adhesion and proliferation of the human fibroblasts MRC-5 cell line. Moreover, all the investigated TiCu(Ag) alloy display bactericidal properties, preventing the growth of both Pseudomonas aeruginosa and Staphylococcus aureus. Results obtained from biological tests have been correlated to the surface structure and microstructure of films. The excellent biocompatibility and bactericidal properties of these multifunctional thin films opens to their use in tissue engineering applications.

Heat shock proteins (Hsps) are highly conserved molecules that are constitutively expressed and upregulated in response to physiological stress conditions. These immunogenic chaperones can have essential functions in fungi, particularly in dimorphic pathogens. Histoplasma capsulatum and Paracoccidioides species are dimorphic fungi that are the causative agents of histoplasmosis and paracoccidioidomycosis, respectively, which are systemic mycoses with significant rates of morbidity and mortality. Current treatment consists of long-term antifungal agents, and there is an urgent need for new therapeutic approaches with higher efficacy, lower toxicity, better biodistribution and improved selectivity. We engineered an immunoglobulin G1 (IgG1) isotype chimeric mouse-human monoclonal antibody, titled ch-MAb 4E12, from the parental IgG2a MAb 4E12, a monoclonal antibody to H. capsulatum Hsp60 that is protective in experimental histoplasmosis and paracoccidioidomycosis models elicited by H. capsulatum var. capsulatum and Paracoccidioides lutzii, respectively. The ch-MAb 4E12 increased phagolysosomal fusion and enhanced the yeasts uptake by PMA differentiated human THP1 macrophage cells in vitro. At low concentrations, the chimeric antibody significantly reduced the pulmonary and splenic fungal burden compared to an irrelevant antibody or no treatment. These results are the first to show that a chimeric mouse-human antibody can modify infection caused by dimorphic fungi.

Cervical cancer is the fourth most common malignancy in women worldwide, although it is preventable with prophylactic HPV vaccination. HPV transmission-dynamic models can predict the potential for global elimination of cervical cancer. The random network model is a new approach that allows individuals to be followed, and to implement a given vaccination policy according to their clinical records. We developed an HPV transmission dynamics model on a lifetime sexual partners network based on individual contacts, also accounting for the sexual behavior of men who have sex with men (MSM). We analyzed the decline in the prevalence of HPV infection in a scenario of 75% and 90% coverage for both sexes. An important herd immunity effect for men and women was observed in the heterosexual network, even with 75% coverage. However, HPV in-fections are persistent in the MSM population, with sustained circulation of the virus among un-vaccinated individuals. Coverage around 75% of both sexes would be necessary to eradicate HPV-related conditions in women within five decades. Nevertheless, the variation in the decline in infection in the long term between vaccination coverage of 75% and 90% is relatively small, suggesting that reaching coverage of around 70-75% in the heterosexual network may be enough to confer high protection. Nevertheless, HPV eradication maybe achieved if men’s coverage is strictly controlled. This accurate representation of HPV transmission demonstrates the need to maintain high HPV vaccination coverage, especially in men, for whom the cost-effectiveness of vaccination is questioned.

Autonomous weapons systems (AWS), sometimes referred to as “killer robots”, are receiving evermore attention, both in public discourse as well as by scholars and policymakers. Much of this interest is connected with emerging ethical and legal problems linked to increasing autonomy in weapons systems, but there is a general underappreciation for the ways in which existing law might impact on these new technologies. In this paper, we argue that as AWS become more sophisticated and increasingly more capable than flesh-and-blood soldiers, it will increasingly be the case that such soldiers are “in the power” of those AWS which fight against them. This implies that such soldiers ought to be considered hors de combat, and not targeted. In arguing for this point, we draw out a broader conclusion regarding hors de combat status, namely that it must be viewed contextually, with close reference to the capabilities of combatants on both sides of any discreet engagement. Given this point, and the fact that AWS may come in many shapes and sizes, and can be made for many different missions, we argue that each particular AWS will likely need its own standard for when enemy soldiers are deemed hors de combat. We conclude by examining how these nuanced views of hors de combat status might impact on meaningful human control of AWS.

The ongoing COVID-19 global pandemic is affecting every facet of human lives (e.g., public health, education, economy, transportation, and the environment). This novel pandemic and citywide implemented lockdown measures are affecting virus transmission, people’s travel patterns, and air quality. Many studies have been conducted to predict the COVID-19 diffusion, assess the impacts of the pandemic on human mobility and air quality, and assess the impacts of lockdown measures on viral spread with a range of Machine Learning (ML) techniques. This review study aims to analyze results from past research to understand the interactions among the COVID-19 pandemic, lockdown measures, human mobility, and air quality. The critical review of prior studies indicates that urban form, people's socioeconomic and physical conditions, social cohesion, and social distancing measures significantly affect human mobility and COVID-19 transmission. During the COVID-19 pandemic, many people are inclined to use private transportation for necessary travel purposes to mitigate coronavirus-related health problems. This review study also noticed that COVID-19 related lockdown measures significantly improve air quality by reducing the concentration of air pollutants, which in turn improves the COVID-19 situation by reducing respiratory-related sickness and deaths of the people. It is argued that ML is a powerful, effective, and robust analytic paradigm to handle complex and wicked problems such as a global pandemic. This study also discusses policy implications, which will be helpful for policymakers to take prompt actions to moderate the severity of the pandemic and improve urban environments by adopting data-driven analytic methods.

Several studies have demonstrated that the p75NTR low-affinity receptor of Nerve Growth Factor (NGF), is produced in abnormally large amounts in several human cancer types. However, the role of p75NTR varies substantially depending on cell context, so that a dual role of this receptor protein in tumor cell survival and invasion, as well as cell death, has been supported in recent studies. Herein we explored for the first time the expression of p75NTR in human specimens (nr=40) from testicular germ cell tumors (TGCTs), mostly seminomas. Nuclear overexpression of p75NTR was detected by immunohistochemistry in tumor tissue as compared to normal tissue, whereas neither NGF nor its high-affinity TrkA receptor was detected. An increased nuclear staining of phospho-JNK, belonging to the p75NTR signaling pathway, and its pro-apoptotic target gene, p53, was concomitantly observed. Interestingly, our analysis revealed that decreased expression frequency of p75NTR, p-JNK, and p53 was related to staging progression, thus suggesting that p75NTR may represent a specific marker of differentiation in TGCTs.

Background: Metastatic cancer is associated with an invariably fatal outcome. However, DeltaRex-G, a tumor- targeted retrovector encoding a CCNG1 inhibitor gene, has induced long term (>10 years) survival of patients with chemo-resistant metastatic pancreatic adenocarcinoma, MPNST, osteosarcoma, B-cell lymphoma, and breast carcinoma. Objective: To evaluate the level of CCNG1 expression in tumors as a potential biomarker for CCNG1 inhibitor therapy. Methods: CCNG1 RNA expression levels were measured in tumors (TCGA, N=9161), adjacent “tissues” (TCGA, N=678) and GTEx normal tissues (N=7187) across 22 organ sites. Differential expression of CCNG1 and Ki-67 in primary (N= 9161) vs metastatic (N= 393) tumors were also compared and particularly in primary (N=103) vs. metastatic (N=367) skin cancer (i.e., melanoma). Results: Enhanced CCNG1 RNA and protein expression were noted in tumors compared to normal analogous counterparts, and CCNG1 expression correlated significantly with that of Ki-67. Further, CCNG1 expression tended to be higher than that of Ki-67 in metastatic vs primary tumors, particularly in skin cancer (melanoma). Conclusions: Taken together, these data indicate that (1) CCNG1 expression is frequently enhanced in tumors when compared to their normal analogous counterparts, (2) CCNG1 and Ki-67 expressions are higher in metastatic vs primary tumors, (3) CCNG1 expression is significantly correlated with that of Ki-67, and (4) CCNG1 may be a stronger marker of metastasis than Ki-67. Phase 2 studies are planned to identify patients who are likely to respond favorably to CCNG1 inhibitor therapy by correlating treatment outcome parameters with CCNG1 expression levels in various cancer types.

Objective: Despite increasing interest in understanding factors influencing awareness, knowledge, and acceptability of the human papilloma virus (HPV) vaccine among Latino parents to date, limited information is available specific to Latino fathers living in the United States. Methods: This descriptive qualitative study explored Latino fathers’ awareness, knowledge, and acceptability of the HPV vaccine for their adolescent children. Data were collected through individual, semi-structured interviews and analyzed using a hybrid method of thematic analysis that incorporated deductive and inductive approaches. Results: Nineteen, majority foreign-born Latino fathers (63.2%; n = 12) fathers of male and female adolescents participated in the study. Four main themes and two subthemes emerged from the analyses. Results found fathers’ low awareness and knowledge of HPV and the HPV vaccine. Results also identified fathers’ positive attitude toward vaccines in general. Moreover, results revealed fathers’ trust in healthcare providers. This trust translated into an increased willingness to vaccinate their children against HPV if recommended by their child’s primary healthcare provider. Conclusion: Findings indicate the need for increased efforts to raise awareness and knowledge among Latino fathers of HPV and the HPV vaccine. In addition, findings underscore the critical role of healthcare providers’ recommendation of the HPV vaccine. Given the limited research focused on Latino fathers, this study’s findings are valuable in building a knowledge foundation needed for developing future studies and interventions to promote the HPV vaccine by targeting Latino fathers living in the United States. Future research should quantify Latino fathers' awareness, knowledge, and acceptability of the HPV vaccine for their children, and preferences for educational interventions to promote HPV vaccination.

Gastrointestinal tumors including pancreatic and colorectal cancers represent one of the greatest public health issues worldwide, leading to million global deaths. Recent research demonstrated that the human heavy chain ferritin (HFt) can encapsulate different type of drugs in its cavity and can bind to its receptor, CD71, in several solid and hematological tumors, thus highlighting the potential use of ferritin for tumor-targeting therapies. Here, we describe the development and characterization of a novel nanomedicine based on the HFt that is named The-0504. In particular, this novel system is a nano-assembly comprising an engineered version of HFt that entraps about 80 molecules of a potent, wide-spectrum, non-camptothecin topoisomerase I inhibitor (Genz-644282). The-0504 can be produced by a standardized pre-industrial process as a pure and homogeneously formulated product with favourable lyophilization properties. The preliminary anticancer activity was evaluated in cultured cancer cells and in a mouse model of pancreatic cancer. Overall results reported here make The-0504 a candidate for further preclinical development against CD-71 expressing deadly tumors

Nowadays, with smartphones people can easily take photos, post photos to any social networks and use the photos for some purposes. This leads to a social problem that unintended appearance in photos may threaten the privacy of photographed person. Some solutions to protect facial privacy in photos have already been proposed. However, most of them rely on different techniques to de-identify photos which can be done only by photographers, giving no choice to photographed person. To deal with that, we propose an approach that allows photographed person to proactively detect whether someone is intentionally/unintentionally trying to take pictures of him/her. Thereby, he/she can have appropriate reaction to protect the privacy. In this approach, we assume that the photographed person uses a wearable camera to record the surrounding environment in real-time. The skeleton information of likely photographers who are captured in the monitoring video is then extracted to be put into the calculation of dynamic programming score which is eventually compared with a threshold for recognition of photo-taking behavior. Experimental results demonstrate that by using the proposed approach, the photo-taking behavior is precisely recognized with high accuracy of 92.5%.

The Human Gut Microbiome is an important host’s component defining its health. These microorganisms are mutualistic symbionts dependent on factors such as host’s age, subsistence models and sociocultural practices, among others. The conjunction of these factors define the microbial ecosystem dynamics. Using a fecal microbiome approach in children, a comparison of two Mexican communities with contrasting lifestyles: “westernized” (Mexico City) and “non-westernized” (Me’phaa indigenous group) was evaluated. The main differences between these two communities are in bacteria associated with different types of diets (high animal protein and refined sugars vs high fiber food, respectively). In addition, the gut microbiome of Me’phaa children showed higher total diversity and the presence of exclusive phyla, such as Deinococcus-Thermus, Chloroflexi, Elusimicrobia, Acidobacteria and Fibrobacteres. In contrast, Mexico City children had less diversity and the exclusive presence of Saccharibacteria phylum which is associated with the degradation of sugar compounds. This comparison allows further exploration of the selective pressures affecting microbial ecosystemic composition over the course of human evolution and the potential consequences of pathophysiological states correlated with westernization lifestyles.

Metastases cause high mortality in several cancers and immunotherapies are expected to be effective in the prevention and treatment of metastatic disease. However, only a minority of patients benefit from immunotherapies. This creates a need for novel therapies that are efficacious regardless of the cancer types and metastatic environments they are growing in. Preclinical immuno-oncology models for studying metastases have long been limited to syngeneic or carcinogenesis-inducible models that have murine cancer and immune cells. However, the translational power of these models has been questioned. Interactions between tumor and immune cells are often species-specific and regulated by different cytokines in mice and humans. For increased translational power, mice engrafted with functional parts of human immune system have been developed. These humanized mice are utilized to advance understanding the role of immune cells in the metastatic process, but increasingly also to study the efficacy and safety of novel immunotherapies. From these aspects, this review will discuss the role of immune cells in the metastatic process and the utility of humanized mouse models in immuno-oncology research for metastatic cancers, covering several models from the perspective of efficacy and safety of immunotherapies.

The interaction of human immunodeficiency virus with human cells is responsible for all stages of the viral life cycle, from the infection of CD4+ cells to reverse transcription, integration, and the assembly of new viral particles. To date, a large amount of OMICs data as well as information from functional genomics screenings regarding the HIV-1-host interaction has been accumulated in the literature and in public databases. We processed databases containing HIV-host interactions and found 2910 HIV-1-human protein-protein interactions, mostly related to viral group M subtype B, 137 interactions between human and HIV-1 coding and non-coding RNAs, essential for viral lifecycle and cell defense mechanisms, 232 transcriptomics, 27 proteomics, and 34 epigenomics HIV-related experiments. Numerous studies regarding network-based analysis of corresponding OMICs data have been published in recent years. We overview various types of molecular networks, which can be created using OMICs data, including HIV-human protein-protein interaction networks, co-expression networks, gene regulatory and signaling networks, and approaches for the analysis of their topology and dynamics. The network-based analysis can be used to determine the critical pathways and key proteins involved in the HIV life cycle, cellular and immune responses to infection, viral escape from host defense mechanisms, and mechanisms mediating different susceptibility of humans to infection. The proteins and pathways identified in these studies may represent a basis for developing new anti-HIV therapeutic strategies such as new small-molecule drugs preventing infection of CD4+ cells and viral replication, effective vaccines, "shock and kill" and "block and lock" approaches to cure latent infection.

Red djulis (Chenopodium formosanum) is a native cereal plant in Taiwan; it contains abundant polyphenols, betalian and dietary fiber. The appearance of red djulis is bright red. Therefore, it is also called the “ruby of cereals”. The antioxidative activity of red djulis extract is well-understood. However, the antiaging function still remains unclear. This study examined the potential of red djulis extract for enhancing collagen secretion and preventing cutaneous aging using red djulis extracts. The red djulis extracts are comprised of an abundant active component that can effectively enhance the ability of collagen secretion of dermal fibroblasts, prevent the glycation of collagen and resist the damage of ultraviolet light exposure. After fibroblast treatment with red djulis extracts, TGM1, KRT1, KRT10 and SOD2 genes were up-regulated significantly by 2.3, 4.3, 4.4 and 27.3 times, respectively, compared to those of the control group. Additionally, it can increase COL1A2 gene expression by 43% and decrease MMP9 gene expression 33%. Therefore, it was demonstrated that red djulis extracts affect gene expressions related to the skin barrier, antioxidation and collagen. Moreover, we found positive effects on skin barrier integrity, endogenous antioxidant activity and skin collagen-preservation. The preparation of the red djulis extracts is environmental friendly and can promote the economic value of Chenopodium formosanum; thus, the proposed extract is suitable for applications in the development of food products, especially beverages, skin care and cosmetic products.

Mast cells (MC) are resident tissue cells found primarily at the interphase between tissues and environment. These evolutionary old cells store large amounts of proteases within cytoplasmic granules, and one of the most abundant of these proteases is the tryptase. To look deeper into the question their in vivo targets, we have analyzed the activity of the human MC tryptase on 69 different human cytokines and chemokines, and the activity of the mouse tryptase (mMCP-6) on 56 mouse cytokines and chemokines. These enzymes were found to be remarkably restrictive in their cleavage of these potential targets. Only five were efficiently cleaved by the human tryptase: TSLP, IL-21, MCP3, MIP-3b and eotaxin. This strict specificity indicates a regulatory function of these proteases and not primarily as unspecific degrading enzymes. We recently showed that the human MC chymase also had a relatively strict specificity, indicating that both of these proteases have regulatory functions. One of the most interesting such regulatory functions may involve controlling excessive TH2 mediated inflammation by cleaving several of the most important TH2-promoting inflammatory cytokines, including IL-18, IL-33, TSLP, IL-15 and IL-21 indicating a potent negative feedback loop on TH2 immunity.

The language we use to describe the past can have a strong influence on the audience’s interpretation of our story. In our experiment, we explore, using 3 different conditions, how the framing and language of an accident report can affect the audience’s proposed solutions to manage the problems found. We find that the approach used to create an accident report can have a powerful influence on the audience’s decision making. Whether we are describing an accident in a similar manner to a crime, using a systems approach or we are accepting of multiple stories which are not linear or coherent, the methods we use to capture and communicate the story have a profound impact on the actions decided upon by the reader.

This study attempts to investigate a method for creating an index from mobility data that not only correlates with the number of people who relocate to a place but also has causal influence on the number of such individuals. By creating an index based on human mobility data, it becomes possible to predict the influence of urban development on future residential movements. In this paper, we propose a method called the travel cost method for multiple places (TCM4MP) by extending the conventional travel cost method (TCM). We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of a neighborhood. However, conventional TCM does not assume that the opportunity cost of travel time varies according to the departure place. In this paper, TCM4MP is proposed to estimate the opportunity cost of travel time with respect to the departure place. We consider such estimation to be possible due to the use of massive mobility data. We assume that the opportunity cost of travel time on non-working days reflects the convenience and amenities of the neighborhood. Therefore, we consider that the opportunity cost of travel time has a causal influence on future residential mobility. In this paper, the validity of the proposed method is tested using the smart card data of public transportation in Western Japan. Our proposed method is beneficial for urban planners in estimating the effects of urban development and detecting the shrinkage and growth of a population.

Sensory evaluation has been widely applied in assessing the quality of many consumer products that directly serve human needs such as food, beverages, clothing, etc. This paper first examined the inherent deficiencies in this approach, due mainly to the essentially subjective nature of human sensory preference. It then argued that instinctively designating certain materials attributes as sensory perceptions is unnecessary; considering every scientific concept is in essence the processed results of our sensory organs/brains, i.e., all quantities were initially human perceptions. Scientific advances have inevitably generated gradual transformation of such human perceptions as warmth and heaviness into objective parameters measurable in physical quantities like temperature and kilograms. Then using existing successful examples, it demonstrated firmly how the sensory attributes can be assessed by more reliable instrumental methods, and envisioned the key steps to turning a perception into scientifically measurable parameter(s).

Pre-Western contact Hawaiʻi stands as a quintessential sustainability example of a large human population that practiced intensive agriculture, yet minimally displaced native habitats that comprised the foundation of its vitality. An explicit geospatial footprint of human-transformed areas across the pre-contact Hawaiian archipelago comprised less than 15% of total land area, yet provided 100% of human needs, supporting a thriving Polynesian society. A post-contact history of disruption of traditional Hawaiian land-use and its supplanting by Western land tenure and agriculture based on ranching, sugarcane, and pineapple, culminated in a landscape, in which over 50% of native habitats have been lost, while self-sufficiency has plummeted to 15% or less. Recapturing the ʻāina momona (productive lands) of ancient times can be accomplished through study of pre-contact agriculture, assessment of biological and ecological changes imposed on Hawaiian social-ecological systems, and conscious planned efforts to increase self-sufficiency and reduce importation. Impediments include the current tourism-based economy, competition from habitat-modifying introduced species, a suite of agricultural pests severely limiting traditional agriculture, and changes in climate rendering some pre-contact agricultural centers suboptimal. Modified agricultural methods will be required to counteract these limitations, and diversified agriculture to broaden the production base, without contributing to further degradation of native habitats.

While the mobile phone is the world’s most popular media device, it is actually not one single medium, but is effectively used as a different medium by different user groups. The article characterizes polymodal differences in mobile apps usage among different user groups, including gender, education, occupation, screen size, and price. We monitored the complete app usage of 10,725 smartphone users for one month each (56 million sessions, recording almost 1 million hours). Our key contribution consists in developing and analyzing a theoretical framework to classify the over 16,000 apps used into five categories. Exploring nine research questions we provide a broad characterization by asking who, with which characteristics, uses which kinds of apps in what extensity and intensity? For example, it is not the young and high occupational grades that use the mobile phone as a human-to-machine computer (including gaming and artificial intelligence tools). Large screen size is related to extensive long sessions, while a small screen size is related to intensive frequent usage. The results go beyond providing ample empirical evidence for the inherently polymodal nature of the mobile phone, but also proposes a framework on how to possibility deal with it analytically.

Excessive vibration of temporary grandstand owing to crowd has lateral rhythmic motions can cause human in panic, which attracted increasing attention in recent years. This paper focuses on experiments that a temporary grandstand occupied 20 participants is oscillated by a shaking table with a series of random waves and induced by crowd with rhythmic swaying motions at lateral direction, respectively. And then a series of vibration perception questionnaires about crowd reaction are obtained. Evaluation of annoying level derives in concept of degree of membership and annoying rate method is proposed, then the human health risk of vibration serviceability of temporary grandstand is assessed with acceleration vibration dose value(VDV). From these results it is clear that standing crowd is more tolerant to vibration than seated crowd. The measured vibrations generated by crowd activities on temporary grandstand can cause panic in crowd. New relationship between the annoyance rate and structural acceleration VDV at logarithmic coordinate is proposed. The findings of this study can be utilized to manage the vibration of temporary grandstand and assess the human health risk.

Curcumin, a natural polyphenolic compound isolated from the plant Curcuma longa, is known to induce autophagy in various cancer cells, including lung cancer. In the present study, we also confirmed by LC3 immunofluorescence and immunoblotting analyses that curcumin triggers autophagy in human lung adenocarcinoma A549 cell line. In parallel with autophagy induction, gene expression of human GD3 synthase (hST8Sia I) responsible for ganglioside GD3 synthesis was markedly elevated in response to curcumin in A549 cells. To investigate transcriptional activation of hST8Sia I associated with autophagy formation in curcumin-treated A549 cells, functional characterization of the 5’-flanking region of the hST8Sia I gene was carried out using luciferase reporter assay system. Deletion analysis demonstrated that the -1146 to -646 region, which includes putative c-Ets-1, CREB, AP-1 and NF-κB binding sites, functions as the curcumin-responsive promoter of hST8Sia I in A549 cells. Site-directed mutagenesis and chromatin immunoprecipitation assay demonstrated that the NF-κB binding site at -731 to -722 was indispensable for the curcumin-induced hST8Sia I gene expression in A549 cells. Moreover, the transcriptional activation of hST8Sia I by curcumin A549 cells was strongly inhibited by compound C, an inhibitor of AMP-activated protein kinase (AMPK). These results suggest that curcumin controls hST8Sia I gene expression via AMPK signal pathway in A549 cells.

Some of the most promising small molecule toxins used to generate antibody drug conjugates (ADCs) include anti-mitotic agents (e.g auristatin and its derivatives) which are designed to attack cancerous cells at their most vulnerable state during mitosis. We were interested to identify a human cystostatic protein eventually showing comparable activities and allowing the generation of corresponding targeted fully human cytolytic fusion proteins. Recently, we identified the human microtubule associated protein tau (MAP tau) which binds specifically to tubulin and modulates the stability of microtubules thereby blocking mitosis and presumably vesicular transport. By binding and stabilizing polymerized microtubule filaments, MAP tau-based fusion proteins skew microtubule dynamics towards cell cycle arrest and apoptosis. This biological activity makes rapidly proliferating cells (e.g cancer and inflammatory cells) an excellent target for MAP tau-based targeted treatments. Their superior selectivity for proliferating cells confers additional selectivity towards upregulated tumor-associated antigens at their surface, thereby preventing off-target related toxicity against normal cells bearing tumor-associated antigens at physiologically normal to low levels. In this review, we highlight recent findings on MAP tau-based targeted cytolytic fusion proteins reported in preclinical immunotherapeutic studies.

As the natural resources are getting exhausted, the concept of sustainable development of region has received increasing attentions, especially for resource-dependent cities. In this paper an innovative method that emergy analysis and IPAT (Human Impact Population Affluence Technology) model were combined in order to analyze the quantitative relationship of economic growth and energy consumption and further to evaluate its overall sustainability level. Taiyuan, a traditional, resource-dependent city in China, is selected as the case study region. The main results show that total emergy of Taiyuan increased from 9.023× 1023 sej in 2007 to 9.116× 1023sej in 2014, with 38% reduction on non-renewable emergy and 125% growth on imported emergy. Regional emergy money ratio (RMB) was reduced by 48% from 5.31× 1013sej/$ in 2007 to 2.74× 1013sej/$ in 2014, indicating that the increasing speed of consuming resources and energy was faster than the increase of GDP, and that Taiyuan’s money purchasing power declined. The lower emergy sustainability index (ESI) indicates that Taiyuan was explored and produced large quantities of mineral resources, which puts more stress on the environment as a consequence, and that this is not sustainable in the long run. The IPAT analysis demonstrates that Taiyuan sticks to the efforts of energy conservation and environmental protection, in order to promote regional sustainable development, it is necessary to take an integrated effort. Policy insights suggest that resourceful regions should improve include energy and resource efficiency, optimizing energy and resourceful structure.

Abstract: Autoimmune diseases (AIDs) are a group of disorders, in which the immune system attacks the body own tissues leading to chronic inflammation and organ damage. These diseases are difficult to treat due to variability in drug PK among individuals, patient responses to treatment, and the side effects of long-term immunosuppressive therapies. In recent years, pharmacometrics has emerged as a critical tool in Drug Discovery and Development (DDD) and precision medicine. The aim of this review is to explore the diverse roles that pharmacometrics has played in addressing the challenges associated with DDD and personalized therapies in the treatment of AIDs. Methods: The review synthesizes research from past two decades on pharmacometric methodologies, including Physiologically Based Pharmacokinetic (PBPK) modeling, Pharmaco-kinetic/Pharmacodynamic (PK/PD) modeling, Disease Progression (DisP) modeling, population modeling, and Quantitative Systems Pharmacology (QSP). The incorporation of Artificial Intelli-gence (AI) and Machine Learning (ML) into pharmacometrics is also discussed. Results: Pharmacometrics has demonstrated significant potential in optimizing dosing regimens, improving drug safety, and predicting patient-specific responses in AIDs. PBPK and PK/PD models have been instrumental in personalizing treatments, while DisP and QSP models provide insights into disease evolution and pathophysiological mechanisms in AIDs. AI/ML implementation has further enhanced precision of these models. Conclusions: Pharmacometrics plays a crucial role in bridging preclinical findings and clinical applications, driving more personalized and effective treatments for AIDs. Its integration into DDD and translational science in combination with AI and ML algorithms holds promise for advancing therapeutic strategies and improving autoimmune patient outcomes.

In the past ten years, the generative artificial intelligence trend has evolved from simply enhancing the creation of audiovisuals using generative adversarial networks to becoming an entirely disruptive force, transforming operations in various industries and markets, including education and business. The introduction and subsequent widespread popularity of Open AI’s ChatGPT in 2022 raised concerns about the use of Generative AI in professional spaces and its impact on authenticity, innovation, data privacy, and integrity. This study seeks to assess the current applications of this disruptive technology in corporate America and build on that knowledge to provide insight into the current innovative practices and the factors driving its use. The research will further outline some risks associated with generative AI technology in business functions and industries and how this technology is being misused in industries worldwide. Following these revelations, recommendations will be made on the need for regulations surrounding the use of generative AI and the future of this technology for researchers and corporations alike. This study aims to equip corporate strategists and leaders with the knowledge needed to embrace AI, be aware of its possible challenges, and find the best ways to use Generative AI to gain competitive advantage. In addition, it seeks to further equip technology experts and professionals with key information about Generative AI to help them make informed choices when working. The study also aims at research management experts and personnel as it contains vital information that will set the foundation for future research.

AbstractThe escalating impact of artificial intelligence (AI) has birthed the fascinating technology of deepfakes, capable of meticulously crafting hyper-realistic audio-visual manipulations. Within the realm of healthcare, this technology presents a double-edged sword, brimming with potential for revolutionizing various facets of care delivery while simultaneously harboring significant ethical and practical challenges. This research delves into the complex narrative surrounding AI deepfakes in healthcare, meticulously analyzing both the exciting opportunities they offer, and the inherent risks associated with their implementation.Background:Traditional healthcare practices face limitations in patient engagement, accessibility, and training efficacy. Deepfakes, with their ability to simulate real-world scenarios and interactions, emerge as a potential solution, offering personalized patient education, immersive mental health interventions, remote consultations with virtual avatars, and realistic training simulations for medical professionals.Objective:This research aims to comprehensively understand the multifaceted impact of AI deepfakes in healthcare systems. It seeks to: Identify and analyze the potential benefits of deepfakes in specific healthcare applications. Assess the ethical and practical challenges associated with deepfake implementation in healthcare settings. Propose recommendations for safe, responsible, and ethical integration of deepfakes within the healthcare system.Results/Conclusion:The research findings illuminate a landscape replete with opportunities and challenges. Deepfakes offer the potential to enhance patient education, personalize mental health interventions, facilitate remote consultations, and revolutionize medical training. However, concerns regarding misinformation, ethical breaches, data privacy, and technical limitations pose significant challenges.The conclusion emphasizes the need for a balanced approach that capitalizes on the innovative potential of deepfakes while mitigating potential harm. Collaborative efforts involving healthcare professionals, technologists, and policymakers are crucial for establishing ethical frameworks, ensuring responsible development, and harnessing the positive power of deepfakes to build a future where healthcare benefits from cutting-edge technology while prioritizing patient well-being and ethical principles.

Deep learning heavily relies on statistical correlations to drive artificial intelligence (AI) innovations, particularly in computer vision applications like autonomous driving and robotics. However, despite providing a solid foundation for deep learning, these statistical correlations can be vulnerable to unforeseen and uncontrolled factors. The lack of prior knowledge guidance can result in spurious correlations, introducing confounding factors and affecting the model's robustness. To address this challenge, recent research efforts have focused on integrating causal theory into deep learning methodologies. By modelling the inherent and unbiased causal structure, causal theory can potentially mitigate the impact of spurious correlations effectively. Hence, this paper explores the basics of causal methodologies in image classification.

Cyber diplomacy is critical in dealing with evolving cybersecurity dangers and possibilities in the digital era. This article investigates the impact of Artificial Intelligence (AI), the Internet of Things (IoT), Blockchains, and Quantum Computing on cyber diplomacy. AI holds the potential for proactive threat identification and response, while IoT enables international information sharing. Blockchains enable secure data sharing and document verification, but they also pose new threats, such as AI-driven cyber-attacks, IoT privacy breaches, blockchain vulnerabilities, and the potential for quantum computing to break encryption. This article conducts case study reviews, in combination with secondary data analysis, and emphasises the value of international cooperation in developing global norms and frameworks to control responsible technology adoption. Cyber diplomacy can promote cybersecurity, protect national interests, and foster mutual trust among nations in the digital sphere by capitalising on possibilities and reducing threats.

This paper presents an innovative testing framework, testFAILS, designed for the rigorous evaluation of AI Linguistic Systems, with a particular emphasis on various iterations of ChatGPT. Leveraging orthogonal array coverage, this framework provides a robust mechanism for assessing AI systems, addressing the critical question, "How should we evaluate AI?" While the Turing test has traditionally been the benchmark for AI evaluation, we argue that current publicly available chatbots, despite their rapid advancements, have yet to meet this standard. However, the pace of progress suggests that achieving Turing test-level performance may be imminent. In the interim, the need for effective AI evaluation and testing methodologies remains paramount. Our research, which is ongoing, has already validated several versions of ChatGPT, and we are currently conducting comprehensive testing on the latest models, including ChatGPT-4, Bard and Bing Bot, and the LLaMA model. The testFAILS framework is designed to be adaptable, ready to evaluate new bot versions as they are released. Additionally, we have tested available chatbot APIs and developed our own application, AIDoctor, utilizing the ChatGPT-4 model and Microsoft Azure AI technologies

Document deskewing is a fundamental problem in document image processing. While existing methods have limitations, such as Hough Line Transformation that can deskew images upside down, and Deep Learning models that require huge amounts of human labour and computational resources and still fail to deskew while taking care of orientation, OCR-based methods also struggle to read text when it is tilted. In this paper, we propose a novel, simple, cost-effective deep learning method for fixing the skew and orientation of documents. Our approach reduces the search space for the machine learning model to predict whether an image is upside down or not, avoiding the huge search space of predicting an angle between 0 and 360. We finetuned a MobileNetV2 model, which was pre-trained on imagenet, using only 200 images and achieve good results. This method is useful for automation-based tasks, such as data extraction using OCR technology, and can greatly reduce manual labour.

This article explores the question of the rate of digital progress in the context of the labor market. Specific features of the current situation are indicated: temporality of socio-technological transformations, which is becoming less and less compatible with the harmonious development of man and society; the pace at which machines acquire intelligence; total devaluation of mental labor; unresolved issue of the role of man in the world of intelligent machines; the criticality of the problem of the labor market, due to its global nature, social significance and the rate of socio-technological changes. It is emphasized that these circumstances in the short term threaten the sustainable development of the global society, whose reactions to the transformation of technological and socio-economic infrastructure are significantly lagging behind. It is concluded that there is an urgent need to strengthen social responsibility, determined by the new ethics of relations between humans and machines with AI, supplemented by the primacy of the dignity of the social role of humans. The authors point out the urgent need to revise ideas about work as the main purpose of a person and about realization in the profession as the main factor that determines the self-esteem of an individual and his social status.

AI is leveraging all aspects of life. Medical services are not untouched. Especially in the field of medical image processing and diagnosis. Big IT and Biotechnology companies are investing millions of dollars in medical and AI research. The recent outbreak of SARS COV-2 gave us a unique opportunity to study for a non interventional and sustainable AI solution. Lung disease remains a major healthcare challenge with high morbidity and mortality worldwide. The predominant lung disease was lung cancer. Until recently, the world has witnessed the global pandemic of COVID19, the Novel coronavirus outbreak. We have experienced how viral infection of lung and heart claimed thousands of lives worldwide. With the unprecedented advancement of Artificial Intelligence in recent years, Machine learning can be used to easily detect and classify medical imagery. It is much faster and most of the time more accurate than human radiologists. Once implemented, it is more cost-effective and time-saving. In our study, we evaluated the efficacy of Microsoft Cognitive Service to detect and classify COVID19 induced pneumonia from other Viral/Bacterial pneumonia based on X-Ray and CT images. We wanted to assess the implication and accuracy of the Automated ML-based Rapid Application Development (RAD) environment in the field of Medical Image diagnosis. This study will better equip us to respond with an ML-based diagnostic Decision Support System(DSS) for a Pandemic situation like COVID19. After optimization, the trained network achieved 96.8% Average Precision which was implemented as a Web Application for consumption. However, the same trained network did not perform like Web Application when ported to Smartphone for Real-time inference, which was our main interest of study. The authors believe, there is scope for further study on this issue. One of the main goals of this study was to develop and evaluate the performance of AI-powered Smartphone-based Real-time Applications. Facilitating primary diagnostic services in less equipped and understaffed rural healthcare centers of the world with unreliable internet service.

There is a lot of pressures from organizations to continually redesign the business processes and the technology infrastructure to support the organization, but to also help organizations manage competing stakeholder needs, changing objectives and behaviour, and so on. A key part of this is making sure that all their activities in the different components of the business are interconnected and that they are moving in the same direction. Enterprise Architecture (EA) is an effective way of dealing with the challenge of designing business activities and supporting IT. This paper will summarize the organization of EA and look more closely at some major components of EA: governance architecture, business architecture, information architecture and technical architecture and consider the overlap and constructive interaction involved. Enterprise Architecture can be best understood through business process redesign. So, it is useful to briefly review the leading frameworks for business process redesign, including COBIT from ISACA, LEAN from the Toyota Group, TOGAF from the Object-Management Group, and the Capgemini Integrated Architecture Framework (IAF). All these frameworks allow us to more successful transformation, to return to the central idea of this paper.

This article examines the profound impact of immigration on Brazil's human capital formation and economic growth from the late 19th century to the early 20th century. It highlights how the influx of European and Asian immigrants filled the labor void created by the abolition of slavery in 1888, fostering agricultural expansion, industrialization, and urbanization. Immigrants brought diverse skills, technologies, and cultural practices that enriched Brazil's socio-economic fabric. The article also compares these historical dynamics with contemporary demographic trends, notably the challenges posed by a declining fertility rate and an aging population. It underscores the necessity of re-evaluating inclusion policies and investing in human capital to sustain economic growth. By drawing lessons from the past, the article suggests that Brazil can navigate current demographic challenges through strategic policy interventions aimed at enhancing human capital as a tool for economic revitalization.

The rapid advancements in the Fourth Industrial Revolution and artificial intelligence (AI) necessitate a transformative approach to leadership in higher education. This paper investigates the current state of leadership in Iraqi universities and proposes strategies to enhance leadership capabilities aligned with technological advancements. Through a comprehensive review of existing literature, qualitative analysis, and quantitative data collection, the study identifies key challenges and opportunities for developing effective university leadership. The findings underscore the importance of strategic human resource management, high-performance work systems, and technological integration in fostering leadership excellence. Practical recommendations for policymakers and educational leaders in Iraq are provided, highlighting the need for strategic investments in leadership development to meet the demands of the evolving educational landscape.

Human-robot collaboration is a new trend in modern manufacture. The safety or human protection is of great significance due to the share of the same workshop between humans and robots. To achieve effective protection, in this paper, a contact force sensor based on the 8-shaped wound polymer optical fiber is proposed. The 8-shaped wound structure can convert the normal contact force to the shrinkage of the 8-shaped optical fiber ring. The macro-bending loss of the optical fiber is used to detect the contact force. Compared with conventional sensors, the proposed scheme has the advantage of high flexibility, low cost, fast response, high repeatability, which shows the great promise on actively alarming collision and passively reducing the hurt.

Background: Breastfeeding is essential for optimal infant health, offering numerous benefits such as infection prevention and enhanced bonding. Despite its importance, challenges exist, particularly for mothers of preterm and very low birth weight (VLBW) infants, necessitating effective lactation support strategies. Initiatives like the Baby Friendly Hospital Initiative (BFHI) and Kangaroo Mother Care (KMC) aim to promote breastfeeding success, while donor human milk (DHM) serves as an alternative bridge while the mother is supported to build up her supply. Adequate lactation support, counseling, and education are vital antenatally, during NICU stays and after discharge to improve breastfeeding rates and infant health outcomes, ultimately contributing to global efforts to reduce neonatal mortality and achieve sustainable development goals. This study explores existing research on factors influencing mothers’ ability to produce breast milk and sustain breastfeeding, with the aim of enhancing lactation support and improving infant health outcomes.Methods/Design: A systematic review will be conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) checklist. Searches will be performed in the following databases: PubMed, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), MEDLINE Ovid via EBSCOhost, Google Scholar, and WILEY online Library) to identify and incorporate primary research articles related to the topic published between 2014 and 2024. Authors will search peer-reviewed articles, gray literature sources, and reference lists to identify eligible studies. Independent abstract and full-text screening by two reviewers will follow the title screening. The analysis of data will be carried out using Review Manager software (version 5.3.5). The I² test will be used to quantify the amount of unexplained heterogeneity. Potential biases related to study size (such as publication bias) will be examined through the application of several techniques, including funnel plots, Egger’s test, Begg’s test, and Trim and Fill analysis.Discussion: Our review represents a singular exploration into exclusive breastfeeding among very low birth weight (VLBW) infants in low- and middle-income countries (LMICs), focusing on breastfeeding assistance methods. With VLBW defined as less than 1500 g, and most low birth weight (LBW) babies born in LMICs, there is a critical need to address feeding challenges and promote optimal nutrition. Despite updated WHO guidelines in 2022, there is still a lack of comprehensive advice for this vulnerable population. Peer support interventions and health worker counseling have shown promise in increasing breastfeeding continuation rates in LMICs, but challenges persist due to workforce shortages and inadequate documentation. Promoting early postpartum milk expression is crucial for milk production and infant health. Our review aims to fill the gap in understanding VLBW mothers’ breastfeeding experiences in LMICs, shedding light on the effectiveness of breastfeeding support methods and identifying areas for further research. Systematic review registration: CRD42024547864

This research introduces a hybrid feature extraction approach that combines Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) methods to address the challenges of reducing feature vector dimensionality and accurately classifying smartphone-based human activities. Moreover, to refine activity classification accuracy, Support Vector Machine (SVM) optimization with Stochastic Gradient Descent (SGD) is employed. LDA, a statistical tool, is leveraged to derive a new feature space for data projection, enhancing class separation and test feature label prediction. The proposed approach, named LMSS, was evaluated using the UCI-HAR dataset and compared with state-of-the-art models. The results demonstrate that the proposed approach outperformed the best-performing method over this dataset. It achieved an accuracy rate of 99.52%, precision of 99.55%, recall of 99.53%, and an F1-score of 99.54%, highlighting the effectiveness of the proposed method in accurately classifying the data.

The key factor that enables pathogenic bacteria to establish successful infections lies largely in their ability to escape the host's immune response and adhere to host surfaces. Vitronectin (Vn) is a multi-domain glycoprotein ubiquitously present in blood and extracellular matrix of several tissues, where it plays important roles as regulator of membrane attack complex (MAC) formation and as mediator of cell adhesion. Vn has emerged as intriguing target for several microorganisms. Vn-binding by bacterial receptors confers protection from lysis resulting from MAC deposition. Furthermore, through its Arg-Gly-Asp (RGD) motif, Vn can bind several host cell integrins. Therefore, Vn recruited to the bacterial cell functions as a molecular bridge between bacteria and host surfaces, where it triggers several host signalling events that could promote bacterial internalisation. Each bacterium uses different receptors that recognise specific Vn-domains. In this review, we update the current knowledge of Vn receptors of major bacterial pathogens, emphasising the role they may play in the host upon Vn-binding. Focusing on the structural properties of bacterial proteins, we provide details on the residues involved in their interaction with Vn. Furthermore, we discuss the possible involvement of Vn adsorption on biomaterials in promoting bacterial adhesion on abiotic surfaces.

In this article, we analyze the relationships that connect graduates from high school, the training system and employment rates and conditions in the Italian regions between 2004 and 2022. The data used refer to the Istat Bes database. The results show that the growth in the number of high school graduates is positively associated with higher university education and employment with the exception of job satisfaction. Subsequently we also present a clusterization with k-Means algorithm confronting the Silhouette Coefficient with the Elbow Method. Finally, we confront seven different machine-learning algorithms for the prediction of the level of graduated from high school. We also present economic policy suggestions to increase schooling in the Italian regions. The results are critically discussed.

Exoskeletons designed to assist patients with activities of daily living are becoming increasingly popular, but still are subject to research. In order to gather requirements for the design of such systems, long-term gait observation of the patients over the course of multiple days in an environment of daily living are required. In this paper a wearable all-in-one data acquisition system for collecting and storing biomechanical data in everyday life is proposed. The system is designed to be cost efficient and easy to use, using off-the-shelf components and a cloud server system for centralized data storage. The measurement accuracy of the system was verified, by measuring the angle of the human knee joint at walking speeds between 3 and 12 km/h in reference to an optical motion analysis system. The acquired data was uploaded to a cloud database via a smartphone application. Verification results showed that the proposed toolchain works as desired. The system reached an RMSE from 2.9° to 8°, which is below most of the comparable system. The system provides a powerful, scalable platform for collecting and processing biomechanical data, which can help to automize the generation of an extensive database for human kinematics.

This paper explores if plants are capable of responding to human movement by changes in their electrical signals. Towards that goal we conducted a series of experiments, where humans over a period of 6 months were performing different types of eurythmic gestures in proximity of garden plants, namely salad, basil, and tomatoes. To measure plant perception, we used the plant spikerbox, a device that measures changes in voltage differentials of plants between roots and leaves. Using machine learning, we find that the voltage differentials over time of the plant predict if (a) eurythmy has been performed, and (b) which kind of eurythmy gestures has been performed. We also find that the signals are different based on the species of the plant. In other words, the perception of a salad, tomato, or basil might differ just as perception of different species of animals differ. This opens new ways of studying plant ecosystems, while also paving the way to use plants as biosensors for analyzing human movement.

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.

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.

Human Platelet lysate, a hemoderivative product rich in growth factors, holds significant promise in tissue engineering and regenerative medicine. However, its practical utility in liquid or gel form is hampered by challenges such as limited stability and handling difficulties. This study aimed to engineer dry and porous aerogels from platelet lysate hydrogel using an environmen-tally friendly supercritical CO2-based shaping process customized for tissue engineering appli-cations. The resulting aerogels demonstrated remarkable mechanical robustness and improved manageability. Notably, they exhibited a high-water absorption capacity. Moreover, these aer-ogels exhibited a sustained and favourable biological response in-vitro. They demonstrated the ability to release functional growth factors, sustaining cellular metabolic activity similar to that of conventional culture conditions, even after prolonged storage. Furthermore, they supported the adhesion and proliferation of murine fibroblasts (BALB-3T3) and the migration of Human Um-bilical Vein Endothelial Cells (HUVEC). In addition to serving as excellent matrices for cell culture, these proposed aerogels also function as efficient growth factor delivery systems. This multi-functional capability positions them as promising candidates for various tissue regeneration strategies. Importantly, the elaborated aerogels can be conveniently stored and considered as ready-to-use products, enhancing their practicality and applicability in regenerative medicine

Keywords: Green human resource management1; Green supply chain management2; Regulation and legislation3; Sustainable development goals4.

Avian metapneumovirus subgroup C (aMPV/C) causes respiratory diseases and egg dropping in chickens and turkeys, resulting in severe economic losses to the poultry industry worldwide. Integrin β1 (ITGB1), a transmembrane cell adhesion molecule, is present in various cells and mediates numerous viral infections. Herein, we demonstrate that ITGB1 is essential for aMPV/C infection in cultured DF-1 cells, as evidenced by the inhibition of viral binding by EDTA blockade, Arg-Ser-Asp (RSD) peptide, monoclonal antibody against ITGB1, and ITGB1 short interfering (si) RNA knockdown in cultured DF-1 cells. Simulation of the binding process between the aMPV/C fusion (F) protein and avian-derived ITGB1 using molecular dynamics showed that ITGB1 may be a host-factor for benefiting aMPV/C attachment or internalization. Transient expression of avian ITGB1 rendered porcine and feline non-permissive cells (DQ cells and CRFK cells, respectively) susceptible to aMPV/C infection. Replication kinetic of aMPV/C in siRNA-knockdown cells revealed that ITGB1 plays an important role in aMPV/C infection at the early stage (attachment and internalization). aMPV/C was also able to infect efficiently human non-small cell lung cancer (A549) cells. This may be due to a consequence of the similar structures of both metapneumovirus F protein-specific motifs (RSD for aMPV/C and RGD for human metapneumovirus) recognized by ITGB1. Overexpression of avian-derived ITGB1 and human-derived ITGB1 in A549 cells enhanced aMPV/C infectivity. Taken together, this study demonstrated that ITGB1 acts as an essential receptor for aMPV/C attachment and internalization into host cells in which facilitates aMPV/C infection.

Antimicrobial resistance (AMR) is a growing public health issue worldwide that affects the world economy. The concern associated with this issue increased during the COVID-19 pandemic. The misuse of antibiotics during the COVID-19 pandemic will have catastrophic implications for the control of AMR. In 2019, the coronavirus illness COVID-19 first appeared in China. COVID-19 infection is a surface-to-surface communicable disease. It is considered the most vital global health disaster of the century. It has rapidly spread around the world and is the greatest challenge for humankind. This chapter discusses the origin, symptoms, transmission, treatment, and recommendations of the COVID-19 disease.

One of the ways to regulate the sensitivity of human cells to the influenza virus is to knock out genes of the innate immune response. Promising targets for the knockout are genes of the interferon-inducible transmembrane protein (IFITM) family, in particular the IFITM3 gene, whose product limits the entry of a virus into the cell by blocking the fusion of the viral and endosomal membranes. In this study, by means of genome-editing system CRISPR/Cas9, monoclonal cell lines with an IFITM3 knockout were obtained based on WI-38 VA13 cells (human origin). It was found that such cell lines are more sensitive to infection by influenza A viruses of various subtypes. Nonetheless, this feature is not accompanied by an increased titer of newly formed viral particles in a culture medium.

Objectives: To evaluate the relationship between the type of conization, the volume and dimensions of the cone, with the persistence/recurrence of CIN 2-3, presence of affected margins and post-cone HR-HPV positivity. Methods: 227 women treated with LLETZ and histologically confirmed CIN2-3 were evaluated between 1996 and 2006 and followed up until June 2016. Age, type of resection according to IFCPC 2011, volume, cone dimensions, margins were studied. of resection, post-cone high-risk human papillomavirus (HR-HPV) status and viral load. Determinants of HR-HPV positivity were estimated using unconditional logistic regression and time to recurrence was assessed using Kaplan-Meier curves. Results: Persistent/recurrent CIN2-3 was found in 12 cases (5.2%), type 1 conization was performed in 81 patients, with 5 recurrences (6.1%), type 2 in 101 patients, with 6 recurrences (5 .9%) and type 3 resection in 45 women, with 1 recurrence (2.2%). Volume and dimensions were not associated with recurrence. The Log-Rank Test did not show a significant difference between the 3 treatments (p= 0.18). The free margins in type 1 were 37%, in type 2 resection 61% and in type 3 71% (p=0.001). Resection type 1 had 15% HR-HPV post positive cone, type 2 reached 16% and type 3 had 9%, this difference being non-significant (p=0.58). The incidence of recurrence at 36 months in type 1 resection was 0.08%, in type 2 treatment it was 0.04% and in type 3 resection it was 0.0%. Conclusions : Type 3 resection had a higher proportion of free margins and lower post-cone HR-HPV positivity, with a lower incidence of persistence/recurrence.

: This study investigates the workplace experiences of mothers of children with intellectual disabilities. These mothers may face challenges in balancing motherhood, disability, and employment. Therefore, it is important to understand the challenges they are facing and the mechanisms they use to cope with caregiving and work responsibilities in managing the stress that develops throughout this ongoing experience. The purpose of this research was to investigate the workplace experiences of single mothers of children with intellectual disabilities. A review of the literature was conducted. For this research, a qualitative methodology was adopted to gain an in-depth understanding of the mothers’ experiences. A narrative method was used for data collection. Thematic analysis was utilized to obtain a clear understanding. The findings suggest that mothers of children with intellectual disabilities face difficulties in balancing between caregiving for their child with a disability and their job responsibilities, in addition to showing that there is a lack of flexibility in the workplace, less awareness from colleagues and bosses of the challenges these mothers face, and a lack of organizational legislation that supports these mothers. According to our findings, workplaces should provide assistance to mothers of children with intellectual disabilities in order to ensure that they are not disadvantaged in their employment.

In recent years, in order to serve as effective solutions to outdoor human thermal environments under the influence of urban heat islands, adaptation measures such as awnings, louvers, directional reflective materials, mist sprays, and evaporative materials have been developed. In this study, a simplified evaluation framework for adaptation measures to urban heat islands is examined. Adaptation measures to urban heat islands are classified into the following three categories; measures to reduce solar radiation incident on the human body, measures to control and cool ground and wall surface temperature, and measures to control and cool air temperature and human body. Case studies are conducted to evaluate the effects of the implementation of cool water circulation sunshade and to examine the adverse effects of cool pavements on the human thermal environment, in addition to the effects of mist sprays on the human body. The effect of the sunshade, watering road, and mist spray, which are typical adaptation measures to urban heat islands, on the human thermal environment was estimated using Wet Bulb Globe Temperature (WBGT) as an indicator for heat stroke prevention and Standard New Effective Temperature (SET*) as an indicator for thermal comfort assessment.

When analyzing user geospatial information through deep learning methods, it is typically necessary to annotate existing geospatial data. Currently, manual annotation methods are commonly employed, suffering from issues related to low efficiency and accuracy. This design is based on the TensorFlow deep learning framework and first realizes the BiLSTM+CRF+AGG deep learning model. Among the models, AGG is the aggregation layer, which is introduced to solve the problem of solid particle size equilibrium. Secondly, based on the characteristics of original data and professional data, an automatic labeling algorithm is proposed. The algorithm first preprocesses the acquired original data set and professional data set, The most valuable unlabeled data set which can make the training model converge quickly is selected from the original data set as the target data set. Sort the target data set based on preset rules and set annotation parameters for the sorted target data set. Based on the set annotation parameters, the corpus is synthesized and used as the annotation result. Thirdly, based on the active learning strategy, a manual annotation auxiliary scheme is proposed, and an Excel generation module that is convenient for manual annotation correction is designed and developed to further improve the efficiency and quality of annotation through iterative processing. The combination of the BiLSTM+CRF+AGG deep learning model and high-quality annotation can accurately identify non-standard, incomplete, or even incorrect geographical information entities. This annotation method has found successful practical application within the context of the research project and has been granted an invention patent.

Visual Patient Avatar ICU is an innovative approach to patient monitoring enhancing the user's situation awareness in intensive care settings. It dynamically displays the patient's current vital signs through changes in color, shape and animation. The technology can also indicate patient-inserted devices, such as arterial lines, central lines and urinary catheters, along with their insertion locations. We conducted an international, multi-center study using a sequential qualitative-quantitative design to evaluate users' perception of Visual Patient Avatar ICU among physicians and nurses. Twenty-five nurses and twenty-five physicians from the ICU participated in the structured interviews. Forty of them completed the online survey. Overall, ICU professionals expressed a positive outlook on Visual Patient Avatar ICU. They described Visual Patient Avatar ICU as a simple and intuitive tool that improved information retention and facilitated problem identification. However, a subset of participants expressed concerns about potential information overload and a sense of incompleteness due to missing exact numerical values. These findings provide valuable insights into user perceptions of Visual Patient Avatar ICU and encourage further technology development before clinical implementation.

Background: In March 2020, a COVID-19 outbreak associated with the Falles Festival in Borriana, Spain, led to significant infections. Methods: In June 2022, we conducted a cross-sectional follow-up study of 473 socially engaged adults aged 18 to 64, examining the cumulative experience after SARS-CoV-2 infection and vaccination responses. Data included demographic details, lifestyle habits, medical history, infection records, and vaccinations from a population-based vaccine registry. Blood samples were analyzed for SARS-CoV-2 antibodies and cellular immunity. We employed a doubly robust inverse weighted probability analysis to estimate the booster vaccine dose's impact on long COVID prevalence and symptom count. Results: 28.1% of participants met the WHO criteria for long COVID, with older individuals showing higher rates. Not complying with long COVID criteria associated with factors including O blood group, higher occupational status, physical activity, three vaccine doses, strong SARS-CoV-2-S-reactive IFNγ‐producing‐CD8+ response, and infection during the Omicron period. Conversely, increased age, high or low social activity, underlying health conditions, a severe initial COVID episode, and reinfection associated with higher long COVID likelihood. A booster dose, compared to one or two doses, reduced long COVID risk by 74% (95% CI: 56.4% to 91.7%) and symptom count by 55.2% (95% CI: 31.6% to 78.7%). Conclusion: Long COVID was prevalent in a significant portion of those who contracted COVID-19, underscoring the need for sustained follow-up and therapeutic strategies. Vaccinations, notably the booster dose, had a substantial beneficial effect on long-term infection outcomes, affirming the vaccination’s role in mitigating SARS-CoV-2 infection consequences.

Our lives are comprised of moment-to-moment activity experiences. According to the Model of Human Occupation (MOHO), our occupational experiences can be affected by volition, which consists of personal causation, values, and interests. This study investigated how momentary volition affected occupational satisfaction and mind-wandering while performing occupations. This study also examined the relationship between momentary volition and the overall life perspectives of life satisfaction and life balance. Undergraduate students participated in this cross-sectional study. The experience sampling method (ESM) was used to measure students’ momentary states such as activity, volition, occupational satisfaction, and mind-wandering. After conducting the ESM, the participants’ life satisfaction was measured using the Satisfaction With Life Scale (SWLS), and their life balance was measured by the Life Balance Inventory (LBI). Forty-two participants and 1,092 sampling data were included in the analysis. Momentary personal causation, values, and interests contributed to occupational satisfaction. Mind-wandering was predicted negatively by interests but positively by personal causation. Momentary interests were positively correlated with SWLS and LBI scores. This study demonstrated that momentary volition was associated with occupational satisfaction and engagement, as well as life satisfaction and balance, in undergraduate students.

There is a growing interest in glial cells in the central nervous system due to their important role in maintaining brain homeostasis both under physiological conditions and after injury. A significant amount of evidence has been accumulated regarding their capacity to exert either pro-inflammatory or anti-inflammatory effects under different pathological conditions. In combination with their known proliferative potential, they contribute not only to the limitation of brain damage and tissue remodeling but also to neuronal repair and synaptic recovery. Moreover, reactive glial cells can modulate the processes of neurogenesis, proliferation, and migration of neurons in the existing neural circuits in the adult brain. By discovering precise signals within specific niches, the regulation of sequential processes in adult neurogenesis holds the potential to unlock strategies that can stimulate the generation of functional neurons, whether in response to injury or as a means of addressing degenerative neurological conditions. Cerebral ischemic stroke, a condition falling within the realm of acute vascular disorders affecting the circulation of the brain, stands as a prominent global cause of disability and mortality. Extensive investigations into glial plasticity and their intricate interactions with other cells in the central nervous system have predominantly relied on studies conducted on experimental animals, including rodents and primates. However, valuable insights have also been gleaned from in vivo studies involving post-stroke patients, utilizing highly specialized imaging techniques. Following the attempts to map brain cells, the role of various transcription factors in modulating gene expression in response to cerebral ischemia is gaining increasing popularity. Although the results obtained thus far remain incomplete and occasionally ambiguous, they serve as a solid foundation for the development of strategies aimed at influencing the recovery process after ischemic brain injury.

Classic mitochondrial DNA phylogenetic and phylogeographic studies on the aboriginal, historical, and extant human populations of the Canary Islands have contributed to reconstructing the origin and settlement on the islands of the pre-European colonizers. The recent use of new ancient DNA targeted enrichment and next-generation sequencing techniques on new Canary Islands samples has greatly improved these molecular results, but it has also revealed significant contamination in the islands' previous aboriginal genetic pool. Following a thorough review of these cases, new phylogeographic analysis revealed the existence of a heterogeneous aboriginal population, asymmetrically distributed across the various islands, and most likely descended from a unique main settlement. These new results and new proposed coalescent ages are compatible with a Roman-mediated arrival driven by the exploitation of the purple on the Canary Islands.

This article presents a state-of-the-art literature review to understand people’s perceptions and opinions of Autonomous Vehicles (AVs) and the factors that influence AV adoption. A strategic literature search was conducted to select articles for this review. Most of the articles were published within the last five years and they used a household questionnaire survey to collect data. Mostly, they used statistical and econometric methods to evaluate the factors that affect people’s intentions to adopt AVs. The results show that psychological factors often appear as the most important internal factors of people’s willingness to adopt AVs. Additionally, other internal factors such as the socioeconomic profile of individuals and their household, and knowledge and familiarity with AV technologies would affect AV adoption tendencies. User attributes also indirectly affect AV adoption by influencing the psychological factors of users. We identify several critical external factors such as opportunities (e.g., safety and security, low congestion, energy use) and challenges (e.g., system failure, privacy breach, and legal issues), while another influential group includes transportation factors (e.g., travel mode, distance, and time), urban form (e.g., urban/rural, density, land use diversity), affinity to new technology, and the institutional regulatory environment. We discuss some recommendations for policy makers, auto industries, and private stakeholders to formulate policies and strategies to increase market share of AVs. Finally, we identify some limitations of previous studies and provide a blueprint for future research on AV adoption.

This study aims to investigate the impact of body heat loss on the thermal and aerodynamic conditions in a whole-body cryotherapy chamber. The underlying hypothesis is that the heat generated by the human body alters the thermal and aerodynamic environment inside the cabin. A numerical study was conducted to test this hypothesis to analyze the thermodynamic exchanges between the human body and the cabin during a 3-minute whole-body cryotherapy session. The computational fluid dynamics (CFD) approach was used to study the unsteady heat transfer between the human body and the interior of the cryotherapy cabin. A thermal boundary condition, based on a mathematical model developed from experimental data, was applied to simulate skin cooling kinetics over time. The post-processing of the 3D results, including temperature, velocity fields, and thermal flux maps at the body surface, provided insight into the thermo-convective mechanisms involved in a whole-body cryotherapy session. The study found that body heat loss significantly affects the temperature fields inside the cabin, leading to global modifications of the aeraulic and thermal conditions. These findings suggest that cryotherapy protocols may need to be adjusted or the cabin set temperature optimized to enhance the therapeutic benefits.

To understand the evolution of the human norovirus GII.P6-GII.6 and GII.P7-GII.6 strains, we analyzed both the RdRp region and VP1 gene in globally collected strains using authentic bioinformatics technologies. A common ancestor of the P6- and P7-type RdRp region emerged approximately 50 years ago and a common ancestor of the P6- and P7-type VP1 gene emerged approximately 110 years ago. Subsequently, the RdRp region and VP1 gene evolved. Moreover, the evolutionary rates were significantly faster for the P6-type RdRp region and VP1 gene than the P7-type RdRp region and VP1 genes. Large genetic divergence was observed in the P7-type RdRp region and VP1 gene compared with the P6-type RdRp region and VP1 gene. The phylodynamics of the RdRp region and VP1 gene fluctuated after the year 2000. Positive selection sites in VP1 proteins were located in the antigenicity-related protruding 2 domain, and these sites overlapped with conformational epitopes. These results suggest that the GII.6 VP1 gene and VP1 proteins evolved uniquely due to recombination between the P6- and P7-type RdRp regions in the HuNoV GII.P6-GII.6 and GII.P7-GII.6 virus strains.

The flora and vegetation of oceanic islands have been deeply affected by human settlement and further landscape modifications during prehistoric and historical times. The study of these transformations is of interest not only for understanding how current island biotas and ecological communities have been shaped but also for informing biodiversity and ecosystem conservation. This paper compares two oceanic insular entities of disparate geographical, environmental, biological, historical and cultural characteristics – Rapa Nui (Pacific Ocean) and the Azores Islands (Atlantic Ocean) – in terms of human settlement and further landscape anthropization. The similarities and differences between these islands/archipelagos are discussed considering their permanent colonization, the possibility of earlier settlements, the removal of the original forests and the further landscape transformations leading to either full floristic/vegetational degradation (Rapa Nui) or major replacement (Azores). This comparison uses evidence from varied disciplines, notably paleoecology, archaeology, anthropology and history, to obtain a holistic view of the development of the respective socioeconomic systems from a human ecodynamic perspective. The most relevant issues still to be resolved are identified and some prospects for future research are suggested. The cases of Rapa Nui and Azores Islands may help set a conceptual basis for ocean-wide global comparisons among oceanic islands/archipelagos.

Virtual reality experiences are frequently created using game engines, yet they are not simple for novices and unskilled professionals who don’t have programming and 3D modeling skills. Concurrently, there is a knowledge gap in software project design for intuitive virtual reality authoring tools, which were supposed to be easier to use. This work compiles design guidelines derived from a systematic literature review to contribute in the development of more intuitive virtual reality authoring tools. We searched the Scopus and Web of Science databases for works published between 2018 and 2021 and discovered 14 papers. We compiled 14 requirement and feature design guidelines, such as Visual Programming, Immersive Authoring, Reutilization, Sharing and Collaboration, Metaphors, and Movement Freedom, among others. The collected guidelines have the potential to either guide the development of new authoring tools or to evaluate the intuitiveness of existing tools. Furthermore, they can also support the development of the metaverse, since virtual content creation is one of its bases.

Tuberculosis (TB) is still a worldwide major health problem and models using non-human primates (NHP) provide the most relevant approach for vaccine testing. In this study we have analysed CT images collected from cynomolgus and rhesus macaques, following exposure to ultra-low dose Mycobacterium tuberculosis (Mtb) aerosols, and monitored them for 16 weeks to evaluate the impact of prior intradermal or inhaled BCG-vaccination on the progression of lung disease. All lesions found (2553) have been classified according to their size and we have subclassified small micronodules (<4.4 mm) as ‘isolated’, or as ‘daughter’ when they are in contact with consolidation (described as lesions ≥ 4.5 mm). Our data links the higher capacity to contain Mtb infection in cynomolgus with the reduced incidence of daughter micronodules, thus avoiding the development of consolidated lesions and their consequent enlargement and evolution to cavitation. In the case of rhesus, intradermal vaccination has a higher capacity to reduce the formation of daughter. This study supports the ‘Bubble Model’ defined with the C3HBe/FeJ mice and proposes a new method to evaluate outcome in experimental models of TB in NHP based on CT images, which would fit a future machine learning approach to evaluate new vaccines.

The real challenge in Human Robot Interaction (HRI) is to build machines capable of perceiving human emotions so that robots can interact with humans in a proper manner. It is well known from the literature that emotion varies accordingly to many factors. Among these, gender represents one of the most influencing one, and so an appropriate gender-dependent emotion recognition system is recommended. In this paper, a two-level hierarchical Speech Emotion Recognition (SER) system is proposed: the first level is represented by the Gender Recognition (GR) module for the speaker’s gender identification; the second is a gender-specific SER block. Specifically for this work, the attention was focused on the optimisation of the first level of the proposed architecture. The system was designed to be installed on social robots for hospitalised and living at home elderly patients monitoring. Hence, the importance of reducing the software computational effort of the architecture also minimizing the hardware bulkiness, in order for the system to be suitable for social robots. The algorithm was executed on the Raspberry Pi hardware. For the training, the Italian emotional database EMOVO was used. Results show a GR accuracy value of 97.8%, comparable with the ones found in literature.

Microbiome First Medicine is a suggested 21st century healthcare paradigm that prioritizes the entire human, the human superorganism, beginning with the microbiome. To date, much of medicine has protected and treated patients as if they were a single species. This has resulted in unintended damage to the microbiome and an epidemic of chronic disorders [e.g., noncommunicable diseases and conditions (NCDs)]. Along with NCDs came loss of colonization re-sistance, increased susceptibility to infectious diseases, and increasing multimorbidity and polypharmacy over the life course. To move toward sustainable healthcare, the human micro-biome needs to be front and center. This paper presents microbiome-human physiology from the view of systems biology regulation. It also details the ongoing NCD epidemic including the role of existing drugs and other factors that damage the human microbiome. Examples are provided for two entryway NCDs, asthma and obesity, regarding their extensive network of comorbid NCDs. Finally, the challenges of ensuring safety for the microbiome are detailed. Under Microbiome First Medicine and considering the importance of keystone bacteria and critical windows of development, changes in even a few microbiota-prioritized medical decisions could make a significant difference in health across the life course.

In recent years in Bangladesh, there has been regular cyclonic event, flooding and erratic pre-monsoons precipitation that has hampered production greatly and forced Bangladesh to import salt from abroad to manage market deficiency. There is much uncertainty about the effects of climate change on the frequency and intensity of small-scale, sudden onset weather phenomena such as heavy rainfall and subsequent loss and damage (L&D). But, several studies indicate that an obvious strong relationship exists between irregular rainfall and associated L&D. Nowadays, severe changing rainfall patterns are observed in Bangladesh, which is rapid-onset in nature, but low exposed in terms of response. The current study explored a ‘double-exposed’ burden combined of both climatic (e.g., uneven rainfall) and non-climatic governance factors (e.g., imperfect trade policy, the absence of risk transfer mechanisms) which are hindering salt production and pushing the country from the aspiration of salt exporting to the net buyer. This chapter mainly assesses the impacts of L&D due to climatic events that are causing overwhelming effects on the well-being of marginal salt farmers at Kutubdia Upazila of Bangladesh. Data were mainly collected through Participatory Vulnerability Analysis (PVA), Key informant interviews (KII), and Sample Surveys (SS). This study would provide insights for improved disaster management policy and an appropriate adaptive measure to address such extreme events as well as to initiate a further study for understanding the nexus of ‘nature and market’ in building resilience among the marginal salt farmers.

Open-plan office (OPO) layouts emerged to allow organizations to adapt to changing workplace demands. We explore the potential for OPOs to provide such adaptive capacity to respond to two contemporary issues for organizations: the chronic challenge of environmental sustainability, and the acute challenges emerging from the great COVID-19 homeworking experiment. We apply a socio-technical systems perspective and green ergonomics principles to investigate the relationship between an OPO environment and the occupants working within it. In doing so, we consider the relevant technical and human factors such as green technology and employee green behavior. We also consider how a green OPO might provide non-carbon benefits such as improving occupant wellbeing and supporting the emergence of a green organizational culture. Our investigation highlights several avenues through which an OPO designed with green ergonomic principles could benefit occupants, the organizations they work for, and the natural environment of which they are a part and on which they depend. We find reason to suspect that green OPOs could play an important role in sustainable development; and offer a research agenda to help determine whether in fact OPOs are another example of how going green is good business.

Groundwater habitats in the Dinaric Karst are home to the only known cave-adapted genus of bivalve mollusks, which currently survives as three distinct species with a highly fragmented distribution. Over the past few decades, Congeria populations suffered a steep decline across their range, as a result of human activities. Here, we identify the most pressing issues concerning the current conservation status of Congeria and identify key priorities for its scientific study. The building of dams and other hydrotechnical constructions have led to a significant decrease in the water inputs that used to supply underground systems where Congeria lives, contributing to a reduction of the cave habitats feasible for bivalve settlement. This is relatively well documented in Popovo polje where, as a result of hydrotechnical interventions on Trebisnjica river, water level drop destroyed well over 99 % of Congeria kusceri population in Zira cave and caused their complete disappearance in other caves. Similar factors are likely to have also affected the sister species Congeria jalzici in the Lika region. In addition, the salinization of Neretva river, lack of proper wastewater management, intense agriculture, tourist exploitation, and additional hydrotechnical plans add to the ongoing decline of the quality of Congeria habitats. These threats are expected to least to drastic reductions in population size within the next few decades, and this situation might be further aggravated by the lack of regulations and active measures for Congeria protection, as well by the limited understanding of its biology. Future scientific studies should be aimed at better elucidating microhabitat preference, defining the range of tolerance of environmental parameters, and assessing the size and genetic viability of existing Congeria populations. However, we highlight that these efforts would most certainly require the collaboration of local authorities and the allocation of appropriate financial resources in order to be effective.

Objectives: Our objective was to assess employer preparedness to protect their employees’ health and safety and promote their well-being in the face of potential disasters in a sample of Northeast United States employers. We developed survey instrument and index based on our model of Total Worker Health® (TWH) Employer Preparedness.Methods: We conducted a 40-question on-line survey with the membership of the Northeast Human Resources Association (US). Human resource managers reported their perceptions of their employers’ preparedness in seven domains: planning, human resources policies, hazard reduction, training, staffing, communications, and resources for resilience. Respondents were categorized by size, sector and reach and their responses scored.Results: Seventy-six individuals representing a diverse group of employers responded to the survey. Mean preparedness was “moderate,” with almost an equal number reporting a high level of preparedness as no preparedness. Employers were most prepared for severe weather events and least prepared for acts of violence. There were no significant differences by sector, size, or reach, although the healthcare sector was more prepared than others.Conclusions: There is a range of TWH® Employer Preparedness among Northeast US employers. The survey and model are important tools that can aid employers in the face of growing threats to “business as usual.”

A crewed mission to and from Mars may include an exciting array of enabling biotechnologies that leverage inherent mass, power, and volume advantages over traditional abiotic approaches. In this perspective, we articulate the scientific and engineering goals and constraints, along with example systems, that guide the design of a surface biomanufactory. Extending past arguments for exploiting stand-alone elements of biology, we argue for an integrated biomanufacturing plant replete with modules for microbial \textit{in situ} resource utilization, production, and recycling of food, pharmaceuticals, and biomaterials required for sustaining future intrepid astronauts. We also discuss aspirational technology trends in each of these target areas in the context of human and robotic exploration missions in the coming century.

Pesticides have a vital contribution to the agricultural industry in Australia. However, pesticide applications may not always selective to its target organism. Exposure to pesticide has been associated with negative impacts to human health. One of the ways to reduce pesticide risk to the population and the environment is through government regulations. To put Australia pesticide regulations into perspective, comparisons were made between Australia and other nation’s pesticides regulations. The EU pesticide regulatory system was chosen for comparison with the Australian’s in the aspect of protecting the population from pesticide exposure. The comparison showed that the assessment to authorize a pesticide in Australia is based on the risk while in the EU, the assessment is based on the hazard of the pesticide. A registered active substance in Australia can be authorized for use indefinitely unless it is nominated for reconsideration while the period of registration of an active substance in the EU lasts for 10 years. In addition, no routine systematic chemical residue surveys are conducted in Australia for food commodities. The results highlight areas for improvement in the Australian pesticide regulatory system from the perspective of controlling undue exposure among the general population.

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMIC) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities – from individual neighborhoods to global regions – that can coordinate local community knowledge with political agency, technical capability, and further research.

In December 2019, pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection emerged in Wuhan City, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused epidemic disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be the sixth international public health emergency. Cellular co-infection is a critical determinant of both viral fitness and infection outcome and plays a crucial role in shaping the host immune response to infections. In this study, sixty-eight public next-generation sequencing libraries from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Using an alignment-free method based on K-mer mapping and extension, SARS-CoV-2 was identified in all except three patients. Influenza A H7N9 (3/68), Human immunodeficiency virus 1 (1/68), rhabdovirus isolate (3/68), Human metapneumovirus (1/68), coronaviruses NL63 (1/68), Parvovirus (1/68), Simian virus 40 (1/68), and hepatitis virus (1/68) genome sequences were detected in SARS-CoV-2 infected patients.

The Sustainable Development Goals (SDGs) raise quality employability, gender equity in access to employment and increase coverage in education, however, in Colombia, high unemployment rates and informality of young people are risks of fulfilling these objectives. This is verified by a study with cohorts on access to employment, labor mobility and entry to quality occupations, through the use of probabilistic models. This study found that young people are less likely to be employed than adults, education has increased in the new generations and allowing them to enter a higher quality occupation, job segmentation and lack of experience of young people are the main cause of unemployment and Women are less likely to be employed than men and to do so in quality jobs. To comply with the SDGs, you must increase coverage in education, make a differential gender policy and expand programs as learners and insert dual education.