Sora is a text-to-video generative AI model, released by OpenAI in February 2024. The model is trained to generate videos of realistic or imaginative scenes from text instructions and show potential in simulating the physical world. Based on public technical reports and reverse engineering, this paper presents a comprehensive review of the model's background, related technologies, applications, remaining challenges, and future directions of text-to-video AI models. We first trace Sora's development and investigate the underlying technologies used to build this"world simulator". Then, we describe in detail the applications and potential impact of Sora in multiple industries ranging from film-making and education to marketing. We discuss the main challenges and limitations that need to be addressed to widely deploy Sora, such as ensuring safe and unbiased video generation. Lastly, we discuss the future development of Sora and video generation models in general, and how advancements in the field could enable new ways of human-AI interaction, boosting productivity and creativity of video generation.
Supply chain efficiency, transparency, and sustainability can be enhanced using blockchain technology. Blockchain enables a company to accurately track raw material origin to finished products, which ensures standard quality and sustainability. Furthermore, blockchain improves partnerships between supply chain stakeholders by providing a confident, common platform for sharing data. The influence of implementing blockchain technology on supply chain sustainability includes reduced wastage, increased resource transparency, monitoring of social standards, and reduced operational costs. The challenges of blockchain implementation include scalability, incorporation with present systems, lack of expertise, safety and confidentiality, and regulatory uncertainty. Companies can tackle these challenges through collaborative approaches and technical improvements. In general, blockchain technology significantly enhances supply chain sustainability and efficiency, which provides opportunities for creative business solutions.
The general objective of the study was to examine the role of technology infrastructureon business performance of Commercial Banks in Kenya. The philosophy that guided the research is positivism philosophy. The study adopted correlational research design. The target population was commercial Banks in Kenya register by the Central Bank of Kenya. The population consisted of all 42 commercial banks in Kenya. Respondents’ population comprised of five top managers from each bank translating to 210 top managers. Slovin’s formula was used to calculate the sample size. Purposive sampling technique was used to select 138 top managers of the 42 commercial Banks in Kenya. This study used a self-administered, closed and open-ended questionnaire to obtain primary data. A pilot study was conducted to test the validity and reliability of the data collection instrument. Quantitative data was collected and analyzed in this study by calculating the response rate with descriptive statistics such as mean, standard deviation, median and proportions using the Statistical Package for Social Sciences (SPSS) version 24). Regression analysis and correlation analysis was used to carry out inferential data analysis to determine the direction and strength of the relationship between the independent and the dependent variables. In order to test the influence of information technology capability on business performance of Commercial Banks in Kenya, the study employed a hierarchical regression analysis with moderation. The study results were presented through use of tables and figures. The study concludes that technology infrastructure has a positive and significant effect on business performance of Commercial Banks in Kenya. The study revealed that hardware/Software, network and database influence business performance of Commercial Banks in Kenya. This implies that improvement in information technology infrastructure (hardware/Software, network and database) would lead to improvement in business performance of Commercial Banks in Kenya. The study recommends that the management of commercial banks in Kenya should ensure they had adequate and up to date hardware/Software to enable their employees improve their productivity.
There has been a great deal of speculation that machine learning might be a general purpose technology. Many other emerging technologies receive similar speculation. However, general purpose technologies are typically identified with the benefit of many years of hindsight. For managers deciding on technology strategy, this classification will come too late. In this paper, we provide an approach to assessing the likelihood that a technology is general purpose before it has widely diffused, so that the classification can be used to inform technology strategy decisions. Using data from online job postings, we compare several emerging technologies in terms of breadth of industries and the importance and breadth of research roles. Our results show that machine learning and related data science technologies are relatively likely to be general purpose.
Cheese has a long history and this naturally fermented dairy product contains a range of distinctive flavors. Microorganisms in variety cheeses are an essential component and play important roles during both cheese production and ripening. However, cheeses from different countries are still handmade, the processing technology is diverse, the microbial community structure is complex and the cheese flavor fluctuates greatly. Therefore, studying the general processing technology and relationship between microbial structure and flavor formation in cheese is the key to solving the unstable quality and standardized production of cheese flavor on basis of maintaining the flavor of cheese. This paper reviews the research progress on the general processing technology and key control points of natural cheese, the biochemical pathways for production of flavor compounds in cheeses, the diversity and the role of yeasts in cheese. Combined with the development of modern detection technology, the evolution of microbial structure, population evolution and flavor correlation in cheese from different countries was analyzed, which is of great significance for the search for core functional yeast microorganisms and the industrialization prospect of traditional fermented cheese.
The ILC Technology Network (ITN) was established in 2022 by the ILC International Development Team, a subcommittee of the International Committee for Future Accelerators, to advance engineering studies toward the realisation of the International Linear Collider (ILC). While the ITN work packages focus on engineering activities for the ILC, their topics are also relevant to a broad range of accelerator applications in particle physics and beyond. These work packages are being carried out now by laboratories in Asia and Europe in close collaboration. This report summarises the current status of the ITN activities.
Semonti Banik, Sajal Chandra Banik, Sarker Safat Mahmud
ABSTRACT The essential factor in developing multi‐robot systems is the generation of an optimal path for task completion by multiple robots. To ensure effective path planning, this paper studies the recent publications and provides a detailed review of the path planning approaches to avoid collisions in uncertain environments. In this article, path‐planning approaches for multiple robots are categorized primarily into classical, heuristic, and artificial intelligence‐based methods. Among the heuristic approaches, bio‐inspired approaches are mostly employed to optimize the classical approaches to enhance their adaptability. The articles are analyzed based on static and dynamic scenarios, real‐time experiments, and simulations involving hybrid solutions. The increasing focus on using hybrid approaches in dynamic environments is found mostly in the papers employing heuristic and AI‐based approaches. In real‐time applications, AI‐based approaches are highly implemented in comparison to heuristic and classical approaches. Moreover, the findings from this review, highlighting the strengths and drawbacks of each algorithm, can help researchers select the appropriate approach to overcome the limitations in designing efficient multi‐robot systems.
Lesley-anne Ey, Neil Tippett, Elspeth McInnes
et al.
Background: Schools are often at the forefront of needing to identify and respond to harmful sexual behavior (HSB). However, there is limited understanding about what training and resources Australian teachers receive on HSB or what they need. Objective: To explore Catholic Education staff's preparedness and their training and resource needs for identifying and responding to HSB in education settings. Participants: and Setting: Seventy-four Catholic education staff answered an online survey, and a further 14 Catholic education pastoral care and leadership staff engaged in single. Method: Online survey and single interviews. Findings: Overall, participants felt most prepared to identify HSB and provide an immediate response to HSB, while they felt least prepared to respond to the parental community and to the families of children affected by HSB. Notably, teachers felt the least prepared to provide ongoing support to children affected by HSB and to respond to families and the parental community in matters concerning HSB. Participants called for training and resources to better support education staff in identifying and responding to HSB. Conclusion: This research has demonstrated that Catholic Education staff feel better prepared in identifying and responding to several elements of HSB than previous research with teachers has indicated, however they still feel inadequate in ongoing responses to children affected by HSB and in responding to parents.
The aim of this study was to investigate the role of point of care ultrasound (POCUS) as an alternative imaging modality to confirm the location of gastric and post-pyloric feeding tubes in patients admitted to the pediatric intensive care unit (PICU). This was a prospective descriptive study performed at a tertiary care children’s hospital. Patients from birth to 17 years of age in whom the medical team placed a temporary enteral feeding tube were eligible for enrollment. The study physician, who was blinded to the radiographic findings, performed a POCUS study of the abdomen. An abdominal radiograph was obtained to confirm the placement in all patients. A total of 13 patients were enrolled, and 14 abdominal POCUS exams were completed. POCUS accurately identified the location of the enteral feeding tube in 10 of the 14 cases. POCUS had a sensitivity and specificity of 85.7% and 57.1%, respectively, in identifying gastric tubes. It had a sensitivity and specificity of 66.7% and 87.5%, respectively, in identifying post-pyloric tubes. No adverse events were reported. This study showed that POCUS had moderate sensitivity and specificity and was, overall, safe. Further studies can assess the level of training needed for improvement in accuracy, and larger studies can help support the findings of this data that POCUS is a safe and accurate alternative to radiographs for enteral feeding tube placement confirmation.
Electric field manipulates the change of droplets wettability on superhydrophobic surfaces, which is widely used in many fields such as electronic zoom microlens and electro wetting displays, and has an important research value. This paper prepared a superhydrophobic acetate film applied electrostatic spinning technique,the maximum contact angle of acetate film is 152.6°, conducted electric field-regulated water droplet wettability change tests, applied voltage to water droplets on acetate film. it was found that the contact angle of the droplets decreased with the increase of the electric field strength, and the electric field regulated the contact angle of the droplets to change in the range of 92.7-142.3°. When the power supply is turned off, the contact angle of the droplet can gradually recover, but not completely restored to the original state.
Abstract Purpose Diabetes mellitus (DM) is the second most common comorbidity in myelodysplastic syndromes (MDS). The purpose of the study was to investigate the clinical characteristics of MDS patients with DM. Methods A retrospective analysis was performed on the clinical data of 890 MDS patients with or without DM. Clinical data, including genetic changes, overall survival (OS), leukemia-free survival (LFS) and infection, were analyzed. Results Among 890 patients, 184 (20.7%) had DM. TET2 and SF3B1 mutations occurred more frequently in the DM group than those in the non-DM group ( p = 0.0092 and p = 0.0004, respectively). Besides, DM was an independent risk factor for infection (HR 2.135 CI 1.451–3.110, p = 0.000) in MDS. Compared to non-DM patients, MDS patients with DM had poor OS and LFS ( p = 0.0002 and p = 0.0017, respectively), especially in the lower-risk group. While in multivariate analysis, DM did not retain its prognostic significance and the prognostic significance of infection was maintained (HR 2.488 CI 1.749–3.538, p = 0.000). Conclusions MDS patients with DM have an inferior prognosis which may due to higher infection incidence, with TET2 and SF3B1 mutations being more frequent in those cases.
George Ntoulas, Charalampos Brakatselos, Gerasimos Nakas
et al.
Abstract Fragile X syndrome (FXS) is the most common cause of inherited intellectual disabilities and the most prevalent monogenic cause of autism. Although the knockout (KO) of the Fmr1 gene homolog in mice is primarily used for elucidating the neurobiological substrate of FXS, there is limited association of the experimental data with the pathophysiological condition in humans. The use of Fmr1 KO rats offers additional translational validity in this regard. Therefore, we employed a multi-level approach to study the behavioral profile and the glutamatergic and GABAergic neurotransmission status in pathophysiology-associated brain structures of Fmr1 KO rats, including the recordings of evoked and spontaneous field potentials from hippocampal slices, paralleled with next-generation RNA sequencing (RNA-seq). We found that these rats exhibit hyperactivity and cognitive deficits, along with characteristic bidirectional glutamatergic and GABAergic alterations in the prefrontal cortex and the hippocampus. These results are coupled to affected excitability and local inhibitory processes in the hippocampus, along with a specific transcriptional profile, highlighting dysregulated hippocampal network activity in KO rats. Overall, our data provide novel insights concerning the biobehavioral profile of FmR1 KO rats and translationally upscales our understanding on pathophysiology and symptomatology of FXS syndrome.
Abstract Background Bronchopleural fistula (BPF) is a rare but fatal complication after pneumonectomy. When a BPF occurs late (weeks to years postoperatively), direct resealing of the bronchial stump through the primary thoracic approach is challenging due to the risks of fibrothorax and injury to the pulmonary artery stump, and the surgical outcome is generally poor. Here, we report a case of late left BPF following left pneumonectomy successfully treated using a right thoracic approach assisted by extracorporeal membrane oxygenation (ECMO). Case presentation We report the case of a 57-year-old male patient who underwent left lower and left upper lobectomy, respectively, for heterochronic double primary lung cancer. A left BPF was diagnosed at the 22nd month postoperatively, and conservative treatment was ineffective. Finally, the left BPF was cured by minimally invasive BPF closure surgery via the right thoracic approach with the support of veno-venous extracorporeal membrane oxygenation (VV-ECMO). Conclusions Advanced BPF following left pneumonectomy can be achieved with an individualized treatment plan, and the right thoracic approach assisted by ECMO is a relatively simple and effective method, which could be considered as an additional treatment option for similar patients.
Dimitra Paranou, Angelos Pentelas, George Doukas
et al.
AbstractTelecommunication (telco) cloud services have emerged as crucial components in the modern digital landscape, offering extensive capabilities for data management, connectivity, and service provision. However, research on telco clouds lacks comprehensive data on the characteristics of production workloads, which is fundamental for designing effective resource management systems, such as workload schedulers and power management mechanisms. To this end, this paper addresses a substantial gap in telco cloud research by creating a comprehensive dataset that encapsulates crucial information regarding the pattern demands of applications within telco data centers. In addition, the proposed dataset contributes to the field by enabling strategic network configuration, optimizing data center sizing, facilitating proactive decision-making for data center operations, but its applicability extends beyond these cases. These examples illustrate the practical value of the dataset in enhancing efficiency, reducing operational costs, and ensuring optimal performance within telecommunication data centers.
This research focuses on decentralized wastewater treatment (DEWAT) technologies for the Philippines that is motivated by the limited suitable wastewater treatment infrastructure in the country. A multi-criteria analysis (MCA), using the Analytic Hierarchy Process (AHP) and Delphi method, was employed to evaluate DEWAT technologies based on life cycle costs and wastewater treatment efficiency parameters such as CODt, BOD5, TSS, NH4-N, TP, and hydraulic retention time. A two-factor Analysis of Variance (ANOVA) without replication was used to assess statistical differences between technologies. The analysis revealed that the Downflow Hanging Sponge (DHS) filter, Multi-Soil Layering (MSL) systems, and Moving Bed Biofilm Reactors (MBBRs) are the top-performing technologies, with no statistically significant differences in their overall performance. The DHS filter ranked highest, excelling in energy efficiency and nutrient removal, making it ideal for resource-scarce environments. MSL systems were noted for their broad-spectrum contaminant removal, while MBBRs demonstrated flexibility and scalability for semi-urban areas. A thorough analysis is carried out for these DEWAT technologies and insights for applicability in the Philippine context are provided.
Pavel Pereslavtsev, Christian Bachmann, Joelle Elbez-Uzan
et al.
There is widespread use of nuclear radiation for medical imagery and treatments. Worldwide, almost 40 million treatments are performed per year. There are also applications of radiation sources in other commercial fields, e.g., for weld inspection or steelmaking processes, in consumer products, in the food industry, and in agriculture. The large number of neutrons generated in a fusion reactor such as DEMO could potentially contribute to the production of the required radioactive isotopes. The associated commercial value of these isotopes could mitigate the capital investments and operating costs of a large fusion plant. The potential of producing various radioactive isotopes was studied from material pieces arranged inside a DEMO equatorial port plug. In this location, they are exposed to an intensive neutron spectrum suitable for a high isotope production rate. For this purpose, the full 3D geometry of one DEMO toroidal sector with an irradiation chamber in the equatorial port plug was modeled with an MCNP code to perform neutron transport simulations. Subsequent activation calculations provide detailed information on the quality and composition of the produced radioactive isotopes. The technical feasibility and the commercial potential of the production of various isotopes in the DEMO port are reported.