Miracle-dz/UniFAR-FTUs huggingface dataset:
A Wastewater Treatment Model for Waste Heat Utilization Assessment

Thermal effluents from power plants can be used to accelerate the treatment of wastewater. Under controlled temperature conditions, retention time in anaerobic digesters and oxidation ponds is minimized. This article presents models for simulating the performance of anaerobic digesters, algae ponds, and the U-tube aeration system. Materials balances are provided for the fermentation of water hyacinths into ethanol and the production of clams and crayfish. Heat balances are performed for an anaerobic digester and for a water hyacinth pond with a protective plastic cover. Flow requirements are examined from both oxygen replenishment and metabolite reduction perspec­ tives. Livestock manure and municipal wastewater can yield methane through anaerobic digestion, and ethanol through the fermentation of water hyacinths grown in wastewater. The nutrient-laden effluents can be used to produce algae, which serves as food for freshwater clams and crayfish. By simulating the biological treatment of wastewater as part of an integrated waste heat utilization complex, we are able to evaluate the benefits of thermal enrich­ ment in terms of the valuable byproducts and waste treatment services provided. Considerable amounts of low grade heat are rejected annually to the environment [1]. The temperature of this low grade heat is too low for most industrial proces­ ses, but it is ideal for living organisms. Fish, livestock, and plants grow faster at * This is the seventh in a series of articles on the utilization of waste heat from power plants. The first article presented our methodology for site-specific assessment of technology options. Subsequent articles described models for simulating the aquaculture, evaporative pad greenhouse, livestock, surface heated greenhouse, and crop drying components of an integrated waste heat utilization complex. The final article in the series will present a summary of our findings.
Assessment of heavy metal distribution, contamination, and ecological risk in mangrove sediments of the Nabq Protectorate, Gulf of Aqaba

This study investigates the distribution and characteristics of heavy metals (Cu, Fe, Cd, Pb, Zn, and Mn) in the mangrove sediments of the Nabq Protectorate in the Gulf of Aqaba. The concentrations of these metals were analyzed at various sampling sites, and their values were compared to reference standards to assess the level of contamination. The results indicate that the studied sites are generally uncontaminated when compared to crustal averages and upper-crust values. Iron (Fe) exhibited the highest concentration, followed by Mn, Pb, Zinc, Cu, and Cd. The sediments in the research area were found to
Determination of in safflower of trace element and heavy metals different habitats in Xinjiang province

Trace element and heavy metals of safflower in different habitats were determinated through flame atomic absorption spectrometr.The research results showed that elements of safflower in different habitats had significant difference,heavy metals of safflower in Hetian habitats and Kashi habitats were higher than safty standard of medical plants in china,the result was provided for quality standard of safflower Xin jiang province.
Product Innovation Among Furniture Firms: The Case of the Private Economy Area

Objective: The objective of this article is to analyze product innovation among furniture firms in the private economy area of Vietnam. Method: We designed a questionnaire related to product innovation among furniture firms in the private economy area. We determined the observed variables (scales) of product innovation among furniture firms based on previous studies and expert interview results. We use both qualitative and quantitative research methods, including descriptive statistics, reliability analysis through the Cronbach alpha coefficient, EFA analysis, the independent T test, and ANOVA analysis. Results: Four attributes of product innovation among furniture firms in the private economy area were quite high. All the attributes of the variables are statistically significant. There is no statistically significant difference in product innovation among furniture firms in the private economy area between these different genders and career seniorities. Conclusions: This research broadens the understanding of the importance of product innovation in the productivity and competitiveness of the furniture firms in the private economy area studied. This research has expanded product innovation among furniture firms in the private economy as an activity with profound business performance impacts. This study can be a basis for other research works and policy design oriented to achieve a comprehensive measurement of business performance and make business strategy in the firm.
Profiling of Canadian Travelers to Asian Travel Destinations

This study profiles a large sample of Canadian travelers who visited nine major Asian travel destinations. The study examines these travelers characteristics and perceptions. Perceptual mapping and correspondence analyses were utilized with a data series of "Canadian Resident Trips Abroad" from the International Travel Survey of Canadians. The results identified critical associations of trip-related characteristics of Canadian travelers for each Asian travel destination selected. There are definite commonalities and differences between Asian travel destinations and Canadian travelers’ behaviors at these destinations. The findings help to provide tourism operators and planners with knowledge for potential positioning and marketing strategies for major Asian travel destinations aimed at specific trip-related characteristics of Canadian travelers.
Benefits, Challenges and Research Recommendations for Social Robots in Education and Learning: A Meta-Review

Social robots exist in various forms but are still not spreading widely to the societal contexts they are envisioned for, such as educational settings. There appears to be a gap between research and practice: A lot of research already demonstrates promising results for using social robots in various domains, but this promise has yet to be realized in “the real world”. The aim of this paper is to form a systematic understanding of the potential and challenges of social robots in the domain of education and learning, which is an intensively researched application domain for social robots. We conducted a meta-review of recent literature reviews (published in 2018-2022), using the PRISMA method. We analyzed 12 review papers that met the defined inclusion criteria by extracting the potential benefits and challenges presented in these reviews. We identify six benefits, five challenges, and six recommendations for future research on social robots in education and learning. These findings emphasize the potential and developments needed to realize the potential of social robots in educational contexts.
Thermohaline Circulation Studies with an Isopycnic Coordinate Ocean Model

Abstract The thermohaline circulation (THC) in a 1000-yr near-global numerical simulation using the Miami Isopycnic Coordinate Ocean Model is analyzed and compared to observations. The model, driven by observed monthly atmospheric climatology, uses potential density referenced to 2000 m (σ2) as the vertical coordinate and accounts for compressibility (thermobaricity) effects. Examination of the three-dimensional mass flux field reveals that the model comes fairly close to quantitatively reproducing a number of global and basin-scale circulation features, such as the vertical–meridional overturning rate in the three major basins, the meridional heat flux, and the transport through the major passages. Methods are presented that allow the construction of composite diagrams revealing quantitative regional aspects of the modeled circulation in potential density space. The diagrams reveal many features of the modeled THC that adhere to observations, the most noticeable shortcoming being a weaker-than-observed n.
Correlation between Biofilm Formation and Multi-Drug Resistance among Clinical Isolates

n=4), Pseudomonas aeruginosa (n=16), Salmonella typhi (n=11), and Staphylococcus aureus (n=68). Associations among isolates capable and incapable of biofilm formation and their multidrug resistance phenotypes were evaluated. Results : Among the 300 clinical isolates tested, 289 isolates (96.3%) exhibited biofilm formation. The most prevalent biofilm-forming organisms were A. baumannii (n=9), Citrobacter koseri (n=1), Coagulase Negative Staphylococcus (CONS) (n=7), E. aerogenes (n=7), E. faecalis (n=15), E. coli (n=137), Klebsiella oxytoca (n=1), K. pneumoniae (n=23), P. mirabilis (n=4), P. aeruginosa (n=16), S. typhi (n=11), S. aureus (n=68), and Streptococcus pneumoniae (n=1). The biofilm-forming isolates demonstrated increased resistance compared to isolates that did not form biofilms. Conclusion : Antimicrobial resistance represents a critical characteristic of infections involving biofilms. The study identified biofilm production in 92.7% of the isolates tested via TCP and in 72.3% of the isolates using the CRA. Furthermore, it was observed that pathogens with multidrug resistance (MDR) exhibited a higher biofilm production tendency than non-producing pathogens.
Mechanism of Interaction between hsa_circ_0002854 and MAPK1 Protein in PM2.5-Induced Apoptosis of Human Bronchial Epithelial Cells

Fine particulate matter (PM2.5) pollution increases the risk of respiratory diseases and death, and apoptosis is an important factor in the occurrence of respiratory diseases caused by PM2.5 exposure. In addition, circular RNAs (circRNAs) can interact with proteins and widely participate in physiological and pathological processes in the body. The aim of this study was to investigate the mechanism of circRNA and protein interaction on PM2.5-induced apoptosis of human bronchial epithelial cells (16HBE) in vitro. In this study, we exposed human bronchial epithelial cells to a PM2.5 suspension with different concentration gradients for 24 h. The results showed that apoptosis of 16HBE cells after PM2.5 treatment was accompanied by cell proliferation. After exposure of PM2.5 to 16HBE cells, circRNAs related to apoptosis were abnormally expressed. We further found that the expression of hsa_circ_0002854 increased with the increase in exposure concentration. Functional analysis showed that knocking down the expression of hsa_circ_0002854 could inhibit apoptosis induced by PM2.5 exposure. We then found that hsa_circ_0002854 could interact with MAPK1 protein and inhibit MAPK1 phosphorylation, thus promoting apoptosis. Our results suggest that hsa_circ_0002854 can promote 16HBE apoptosis due to PM2.5 exposure, which may provide a gene therapy target and scientific basis for PM2.5-induced respiratory diseases.
Using seismic mixtures to extract tilts and recover estimates of ground displacements

One of the goals of seismology is to understand the behaviour of the earth’s movements during the occurrence of an earthquake. This research focuses on the recovery of better estimation of the true ground displacements as the tilt components are inherent in recorded acceleration time histories. The raw acceleration time histories recorded in seismograms of the near field earthquake are contaminated by the effects of tilt time histories. The effects of tilt time histories cause non–zero baseline errors in seismic records thereby providing offset in the ground velocity although the final velocity never ends to zero and ground displacement diverges from the constant value. To perform baseline corrections it is therefore necessary to remove the tilt and noise components. Tilt separation was undertaken using a model designated the Tilt Separation – Independent Component Analysis (TS-ICA) model, and an enhanced version of the Extended Generalised Beta Distribution (EGBD) model. Several source distributions such as Normal, Gaussian, Non-Gaussian, Sub and Super Gaussian and skewed distribution with zero kurtosis has been modelled using EGBD and separated using EGBD-ICA. In order to refine the EGBD-ICA model, a randomised mixing matrix was introduced in the existing EGBD-ICA model using MATLAB. With the introduction of the mixing matrix, the consistency of the source separation has improved and particularly tilt separation was convincing for both artificial tilt separation from the Hector Mine earthquake data and real-time tilt separation from the real-time acceleration time histories. The tilt separation and de-noising by the TS-ICA model has given better estimates of ground displacement than the tilt contaminated ground displacement. The estimated tilt angle can provide further scope for seismic scientists and civil engineers to improve their understanding of the tilt behaviour during an earthquake and can add another dimension to their research by making it possible to improve the stability of the building structures in the seismically active regions and areas which are potentially prone to earthquake.
Generating a potent inhibitor against MCF7 breast cancer cell through artificial intelligence based virtual screening and molecular docking studies

Artificial Intelligence (AI) has been widely adopted by pharmaceutical industry to aid rationally drug design and development by fostering the quick delivery of drug targets with optimized structures in spite of huge chemical space of >10 60 drug molecules. Tamoxifen, Selective Estrogen Receptor Modulator (SERM), is the drug for breast cancer cell, MCF 7 with many side effects. Tamoxifen may cause side effects like increased bone or tumor pain, pain or reddening around the tumor site, hot flashes, nausea and excessive tiredness etc . , Therefore, compound which can resist ER’s bioactivity is considered as an important target for treating breast cancer. In this study, AI based Virtual Screening (VS) method using an efficient Generative Neural Network (GNN) model has been experimented to generate high inhibitory potential hit drug-like inhibitors. Physicochemical, Pharmacokinetic and toxicity analysis are carried out for conforming the sub-selection of drug-likeness of inhibitors. Additionally, Molecular Docking studies with DNA (355D) and protein (3EU7) are performed for the evaluation of binding affinity, prediction of intermolecular interactions and inhibition constant. The docked results of the inhibitor M22 (methyl 2-[(2-benzoylphenyl) carbamoyl] benzoate) has low free energy of binding (-8.61 Kcal/mol and -8.05 Kcal/mol) and low Inhibition constant, Ki, value (0.486 μ M and 1.25 μ M) as compared to Tamoxifen (-6.7 Kcal/mol & -5.62 Kcal/mol and 12.2 μ M & 75.85 μ M). Thus, minimum amount of the M22 inhibitor is enough as compared to Tamoxifen and M22 has 3 benzene rings, extended conjugation, amide linkage and huge number of labile electrons which facilitates as a potent drug. This study provides a greenish path to synthesise a potent inhibitor, M22, for further experimental studies rather than preparing number of inhibitors on the atom economy way.
ASSESSMENT OF COMMUNITY AWARENESS AND INVOLVEMENT IN SPORT TOURISM: A CASE STUDY OF THE OBUDU MOUNTAIN RACE, NIGERIA

The Obudu Mountain Race is the only mountain running race in Nigeria. It was conceived as a marketing tool to increase tourists flow to the Obudu Mountain Resort and Cross River State in general. It is generally believed that one current that drives the success of events tourism is the role of host organizations. And of particular interest is the role of the host community in the organization and management of events. This concern is imperative because of the dynamics of community involvement in event organization. The success and sustainability of the Obudu Mountain Race to a large extent depends on the level of community awareness and involvement in the organization of the event. This has motivated the authors to carry out an exploratory research with a view to determining the extent to which the Obudu Mountain Resort Support Communities (OMRSCs) are involved in the organization and management of the Obudu Mountain Race. In depth interviews were done on community leaders who served as informant. Data were collected from six communities’ representatives. The result shows that: communities are fairly aware of the existence and history of the event, communities had positive perception of the event and destination attributes, communities were not involved in decision making concerning the organization and management of the event, communities are cognizant of the expected benefits derivable from the staging of the mountain race.
Between the Authentic and Artificial: From the Perspective of Contingency

How to deal with a contingency? A contingent situation plays a vital role in challenges with uncertainty and unpredictability. This is because contingency requires the subject to be adaptive and flexible in the given condition. Regarding the development of robotics, soft robotics is highly anticipated to be more adaptable and flexible to contingency with its bodily inputs. In contrast, material-wise, conventional hard robotics may fit more for fixed, stable, static, or predictable situations. The latest development in new materials has opened a window for more usable and useful artificial body parts as advanced tools. This short article first highlights the types of artificial body parts and summarises the role of contingency in robotics development. In addition, it analyses the various phases of the concept of the embodied mind in link with contingency. Additionally, for further discussion, it questions ethical, moral, and legal aspects regarding the future development of artificial body parts.
Cancer Pain and Non-Invasive Brain Stimulation—A Narrative Review

Background and Objectives: Pain is the most prevalent symptom in cancer patients. There is a paucity of data regarding non-invasive brain stimulation (NIBS) for the treatment of chronic pain in patients with cancer. The purpose of this article is to review the techniques of NIBS and present the published experiences of the oncological population. Materials and Methods: Databases including MEDLINE, Scopus, Web of Science, and the Cochrane Library were searched for articles on cancer patients with pain that was managed with non-invasive brain stimulation techniques. We included articles in English that were published from inception to January 2023. As studies were limited in number and had different designs and methodologies, a narrative review was considered as the best option to integrate data. Results: Four studies focusing on transcranial magnetic stimulation, six articles on transcranial direct current stimulation, and three articles regarding cranial electric stimulation were found and reviewed. Conclusions: Data are limited and not robust. Further studies in this field are required. Guidelines on NIBS for non-malignant chronic pain conditions provide good premises for cancer-related chronic pain.
Exploring the Design of Robot Mediation with Bodily Contact for Remote Conflict

Interpersonal conflicts are often more difficult to mediate when communicating remotely. The lack of social cues and external mediation makes it difficult for positive conflict behaviors to occur. To this end, robots have been shown to have the potential as mediators. In this paper, we attempt to discuss how to design appropriate bodily contact interactions for the different roles of a robot mediator so as to facilitate the effectiveness of its mediation. We first conduct a pilot interview to probe the potential roles and design elements of robot contact in this study. Then, we explore the relationship between these roles and design elements through a 16-participant design workshop. Finally, we analyze these findings and propose design suggestions for future robot mediator design.
Reconstructing Millennial-Scale, Regional Paleoclimates of Boreal Canada during the Holocene

Abstract Regional paleoclimate reconstructions for northern Canada quantify Holocene climate variability on orbital and millennial time scales and provide a context to better understand the current global warming. The reconstructions are based on available pollen diagrams from the boreal and low Arctic zones of Canada and use the modern analog technique (MAT). Four regional reconstructions document the space–time evolution of the climate during the Holocene. Highest summer and winter temperatures anomalies are found in central Canada during the early Holocene. Eastern Canada was relatively cool in the early Holocene, whereas central Canada was warmest at that time. Labrador was relatively dry in the early to mid-Holocene during which time western Canada was relatively moist. Millennial-scale temperature variations, especially the Medieval Warm Period and Little Ice Age are seen across the continent, with some suggestion of time-transgressive changes from west to east. At the millennial scale, precipitatio.
BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach

Compiler optimization plays an increasingly important role to boost the performance of machine learning models for data processing and management. With increasingly complex data, the dynamic tensor shape phenomenon emerges for ML models. However, existing ML compilers either can only handle static shape models or expose a series of performance problems for both operator fusion optimization and code generation in dynamic shape scenes. This paper tackles the main challenges of dynamic shape optimization: the fusion optimization without shape value, and code generation supporting arbitrary shapes. To tackle the fundamental challenge of the absence of shape values, it systematically abstracts and excavates the shape information and designs a cross-level symbolic shape representation. With the insight that what fusion optimization relies upon is tensor shape relationships between adjacent operators rather than exact shape values, it proposes the dynamic shape fusion approach based on shape information propagation. To generate code that adapts to arbitrary shapes efficiently, it proposes a compile-time and runtime combined code generation approach. Finally, it presents a complete optimization pipeline for dynamic shape models and implements an industrial-grade ML compiler, named BladeDISC. The extensive evaluation demonstrates that BladeDISC outperforms PyTorch, TorchScript, TVM, ONNX Runtime, XLA, Torch Inductor (dynamic shape), and TensorRT by up to 6.95×, 6.25×, 4.08×, 2.04×, 2.06×, 7.92×, and 4.16× (3.54×, 3.12×, 1.95×, 1.47×, 1.24×, 2.93×, and 1.46× on average) in terms of end-to-end inference speedup on the A10 and T4 GPU, respectively. BladeDISC's source code is publicly available at https://github.com/alibaba/BladeDISC.