Miracle-dz/UniFAR-FTUs huggingface dataset:
Detoxi cation of E-waste polluted site using cashew nut shell-based activated carbon

11 This study considered the potential use of activated carbon (AC) produced from 12 cashew nuts for remediation of electronic waste (E-waste) polluted soil sites at 13 Agbogbloshie, Accra, Ghana. The AC supplied by Climate-Environmental Research 14 and Technology (CLERET) Laboratory, one of the research and development (R&D) 15 umbrellas of Explore Scientific Innovations Ltd., Ghana. It was prepared by a two16 stage process involving wood-fired reactor for thermal pyrolysis at temperature 17 ranging from 800-1000 C, followed with activation with oxidizing gas generated by 18 wood-fired steam boiler at 160 C and 7.5 atm pressure for 30 minutes. The product 19 was characterized based on bulk density, particle size, iodine number, electrical 20 conductivity (EC), porosity, and pH. Three replicates of soil samples were scooped 21 from at a depth of 0-15 cm using a soil auger from two randomly selected sites. The 22 samples were digested with 10 ml of ternary solution (20 ml of HClO4; 500 ml of 23 HNO3; 50 ml of H2SO4) on a hot plate at 90°C for 30 minutes to an hour and analyzed 24 for selected heavy metals (Pb, Fe, Cu, Cr and Cd) using Atomic Absorption 25
ABSOLUTE PERMEABILITY UPSCALING NEAR WELLS IN FINE GRIDS REPRESENTING PETROLEUM RESERVOIRS

Upscaling techniques are commonly used to adapt th e fine grid properties to coarser grids with an ade quate number of cells in order to be used in reservoir simulation. The property usually submitted to upscaling is abso lute permeability. Although various upscaling techniques are available for abso lute permeability, in practice, it is difficult to select the most adequate for each type of reservoir heterogeneity. In fact, there is no general rule that is applicable to all types of petroleum reservoirs. An important aspect to be considered in upscaling is the fine gr id cells that contain wells. The usual techniques u sed to calculate equivalent permeability are approprieted only for cells far fr om the wells. The well grid cells require a special treatment during upscaling or reservoir simulation in order to take into account the radial flow pattern near wells. In this work, s ome fine grids with different heterogeneities are submitted to upscaling. These f ine grids and their respective coarse grids are sim ulated and the results obtained by both grids are compared. The influence of specia l treatmens applied to well blocks in coarse grids is evaluated. It is possible to observe the great importance of the well block in C umulative Oil and Water Production for producer wel ls, being very difficult to define a general rule that is suitable to all reservoir wells.
PREVENTION OF BLOOD-BORNE INFECTIONS AMONG NURSES AT DR. IVAN SELIMINSKI HOSPITAL, SLIVEN

INTRODUCTION: The occupational activities of nurses entail a daily exposure to infectious and non-infec-tious factors that can affect their health. Blood-transmitted pathogens caused by occupational exposure pose the most serious threat. Prevention strategies include vaccinations and universal precaution measures. AIM: The aim of this study is to assess vaccinations and other precautionary measures against blood-borne infections: HBV, HCV, HIV, and the attitude towards those among nurses at Dr. Ivan Seliminski Hospital, Sliven. MATERIALS AND METHODS: We used an individual anonymous survey among 55 nurses working in different wards of the Hospital. RESULTS AND CONCLUSION: A large number of nurses at the hospital have had an HBV immunisation (69%). A significant proportion have also had serologic status testing for HCV and HIV (58%). Most nurses indicated they have had immunisation and testing as a precautionary measure.
Secondary metabolites and related genes in Vitis vinifera L. cv. Tempranillo grapes as influenced by ultraviolet radiation and berry development

The effects of UV radiation on Vitis vinifera cv Tempranillo grapes were studied under field conditions as influenced by ultraviolet (UV) band (UV-A and UV-B), UV-B level (ambient vs enhanced), grape phenological stage (pea-size, veraison, and harvest), grape component (skin, flesh, and seeds), and fraction from which phenolic UV-absorbing compounds (UVACs) were extracted (soluble vs insoluble). Ambient UV-B levels caused stronger effects than ambient UV-A. These effects included increases in flavonol contents (particularly quercetins and kaempferols),
The Direct and Indirect Impact of Relational Ties on Innovation Performance: An Empirical Study in China

This paper aims to understand the underlying mechanisms by which relational ties influence firm innovation. Companies in China rely much on relational ties to implement business strategies. Combining social network theory with dynamic capability perspective, we build a model that analyzes the direct and indirect impact of relational ties (business ties and service ties) on innovation performance through supply chain adaptability. We further analyze that technological turbulence and dysfunctional competition influence the relationships between relational ties and supply chain adaptability. We test these relationships using data collected from 300 manufacturers in China. The results show that service ties plays a relatively more important role than business ties in enhancing innovation performance directly. Interactions between business ties and service ties significantly influence innovation performance. Moreover, our results demonstrate that supply chain adaptability fully mediates the relationship between business ties and innovation performance but partially mediates the relationship between service ties and innovation performance. Our results show that technological turbulence positively moderates the relationships between business/service ties and supply chain adaptability. In addition, dysfunctional competition negatively moderates the relationship between business ties and supply chain adaptability. Overall, our findings contribute to the understanding of the roles of relational ties in supply chain.
Iliac Bone Harvesting Techniques for Bone Reconstruction. Comparative Study Between Tricortical Bone Harvesting vs Trapdoor Technique

Objective: To investigate the effects of trapdoor-procedure-based bone harvesting and tricortical iliac bone harvesting on the iliac bone-graft donor site pain experienced by patients and their clinical effects. Methods: A retrospective analysis was performed using the clinical data of 65 patients with tibial plateau fractures who received autologous iliac bone-supporting grafts in two hospitals between January 2014 and January 2019. The patients who received trapdoor-procedure-based bone harvesting (34 cases) were in the experimental group, and those who received tricortical iliac bone harvesting (31 cases) were in the control group. This study compared differences in iliac bone-graft donor site incision length, intraoperative blood loss, amount of bones harvested, operation time, and postoperative complications between the two bone-harvesting methods. Subsequently, it evaluated the pain experienced by the two patient groups in their iliac bone-graft donor sites and their clinical effects. Results: One week after surgery, the differences between the iliac bone-graft donor site pain score (measured using SF-MPQ-2) of the experimental group and the control group were not statistically different. However, 3 weeks, 5 weeks, and 3 months after surgery, the iliac bone-graft donor site pain scores of the experimental group were signi ﬁ cantly lower than those of the control group. The iliac bone-graft donor site incision length and operation time of the experimental group were not signi ﬁ cantly different from those of the control group. However, the iliac bone-graft donor site intraoperative blood loss, amount of bones harvested and the incidence of complications of the experimental group were signi ﬁ cantly lower than those of the control group. Conclusion: Trapdoor-procedure-based bone harvesting has lower donor site pain, intraoperative blood loss, and postoperative complications. However, for bone grafting in regions with signi ﬁ cant bone loss, tricortical iliac bone harvesting remains the optimal option.
CHEMOMETRIC APPROACH TO OPTIMIZATION OF WHITE CABBAGE FERMENTATION HEMOMETRIJSKI PRISTUP OPTIMIZACIJE PROCESA FERMENTACIJE BELOG KUPUSA

The aim of the present work is to optimize fermentation process of whole cabbage heads of white cabbage (cultivar „Futoški“ and hybrid “Bravo“ were considered within this research). Both cabbages were subjected to fermentation process, with addition of 1- 2% NaCl, at temperature 18-22 o C. Different organic acids contents (oxalic – OK 1 , lactic – OK 2 , acetic – OK 3 , malic – OK 4 , citric – OK 5 , succinic – OK 6 and formic– OK 7 ) within cabbage leaves and brine were monitored during 80 days. Principal component analysis exerted good discrimination capabilities for different samples of „Futoški“ and hybrid “Bravo“ cabbage heads fermentation process, while standard score helped in optimal process parameters determination.
Peroxisome Proliferator-Activated Receptor g -Dependent Repression of the Inducible Nitric Oxide Synthase Gene

The peroxisome proliferator-activated receptor g (PPAR g ) is a member of the nuclear receptor superfamily that activates target gene transcription in a ligand-dependent manner. In addition, liganded PPAR g can inhibit transcription of genes induced by gamma interferon (IFN- g ) and/or lipopolysaccharides (LPSs), including the inducible nitric oxide synthase (iNOS) gene. Inhibition of the iNOS promoter is achieved partially through an- tagonizing the activities of NF- k B, AP-1, and STAT1, which are known to mediate effects of LPS and IFN- g . Previous studies have suggested that transrepression of these factors by nuclear receptors involves competition for limiting amounts of the general coactivators CREB-binding protein (CBP) and p300. CBP and p300 are thought to be recruited to nuclear receptors through bridging factors that include SRC-1, although CBP also interacts directly with PPAR g through its amino terminus. These observations have raised questions concerning the involvement of SRC-1-like factors in CBP recruitment and transrepression. We here provide evidence that PPAR g ’s ability to repress iNOS transcription requires the ligand-dependent charge clamp that mediates interactions with CBP and SRC-1. Single amino acid mutations in PPAR g that abolished ligand-dependent interactions with SRC-1 and CBP not only resulted in complete loss of transactivation activity but also abolished transrepression.
THE EFFECT OF GOVERNMENTAL ACCOUNTING REPORTS ON INCUMBENTS SUCCESS: A STUDY OF INDONESIA LOCAL ELECTION The Of Governmental On A

This research wants to predict the incumbents ’success in an electoral situation using the governmental accounting disclosure. The disclosure is covering financial and non-financial performance. The research sample is 1566 local elections in Indonesia, between 2005 and 2018. The research result shows that internal control weakness and performance score are significant for the incumbents’ success. Meanwhile, the audit opinion, non-compliance finding, and accountability score are insignificant. The result shows that less of internal control weakness and greater performance can predict the incumbents’ success. However, this research has limitations that assuming the voters are rational.
ANALYSIS AND REASONING OF DATA IN THE DATABASE USING FUZZY SYSTEM MODELLING

— In this paper a new fuzzy system modeling algorithm is introduced as a data analysis and approximate reasoning tool. The performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison two benchmark data sets from the literature, namely the automobile mpg (miles per gallon) prediction and Box and Jenkins gas-furnace data are used. The comparisons demonstrated that the proposed algorithm can be successfully applied in system modeling.
Topical Photodynamic Therapy Generates Microvesicle Particles

Oyebanji, Oladayo Ayobami. M.S., Department of Pharmacology and Toxicology, Wright State University, 2020. Topical Photodynamic Therapy Generates Microvesicle Particles . Photodynamic therapy (PDT) involves the use of light at an appropriate wavelength acting on a photosensitizing chemical to cause cell death via generation of reactive oxygen species. PDT has been useful in the management of skin conditions (like acne, psoriasis) and cancers like superficial skin, esophageal and non-small cell lung cancers. In addition to these therapeutic effects, previous murine studies from our group have demonstrated that topical PDT induces immunosuppression in vivo. Thus, topical PDT of skin can generate systemic effects through unknown mechanisms. Our group showed that PDT induces an immunosuppressive effect which occurs partly via Platelet-Activating Factor Receptor (PAFR) signaling. Of importance, PAFR signaling can generate Microvesicle particles (MVP). MVPs are small extracellular membrane-enclosed particles believed to mediate cell-to-cell communication via the transport of bioactive signaling substances. The present studies tested if PDT could generate MVP release. Our studies used in vitro, ex vivo (human skin explants) and in vivo (murine) models. PDT increased MVP release across the different cell lines tested in vitro as well as treatment of human skin explants ex vivo. Murine studies also revealed a significant increase in MVP levels in skin and blood following PDT treatment. We also found a limited role for PAFR in this PDT-generated MVP release. These studies reveal a consistent production of MVPs following PDT and thus, provide insights into a possible novel mechanism whereby PDT exerts systemic effects via the generation of MVPs.
Voice Commerce: Understanding Shopping-Related Voice Assistants and their Effect on Brands

consumer behavior and media possess insights that are likely transferable to voice assistants, the peculiarities of this technology require new theories that are not yet fully developed (Kumar et al., 2016). This study sheds light on the potential impact that the diffusion of shopping-related voice assistants has on consumer brands. The main contribution is to reconcile existing interdisciplinary literature and review how voice assistants may alter market dynamics as emerged during in-depth interviews with 31 AI-aware executives. Key conceptual nodes related to the dual agency/mediator role of voice assistants and their anticipated effects on consumer brands are explored.
Analysis of the Multimode Fiber at Low-Frequency Passband Region

Multimode fibers have been used in communication systems for more than 40 years. The characteristics of such fibers have been investigated and it has shown that not just the 3-dB modal bandwidth of multimode fibers, but the high-frequency passbands can also be used to carry the signal; resulting in an increase of the data rate transmitted by a multimode fiber. However, the low-frequency passbands of multimode fibers have not been studied intensively. In this work, the characteristics of low-frequency passbands of multimode fibers are considered. The peak frequency, the amplitude, and the bandwidth of each possible passband are studied. From the simulation results, it is found that these parameters can be estimated. The approximation formulas for these three important parameters are given. Using the results found, the low-frequency passbands of multimode fibers can be utilized; thus, in comparison to the data rate obtained from the 3-dB modal bandwidth, a higher data rate for transmitting a signal over a multimode fiber can be increased at least 3 folds.
Rethinking Attention Mechanism in Time Series Classification

Attention-based models have been widely used in many areas, such as computer vision and natural language processing. However, relevant applications in time series classification (TSC) have not been explored deeply yet, causing a significant number of TSC algorithms still suffer from general problems of attention mechanism, like quadratic complexity. In this paper, we promote the efficiency and performance of the attention mechanism by proposing our flexible multi-head linear attention (FMLA), which enhances locality awareness by layer-wise interactions with deformable convolutional blocks and online knowledge distillation. What's more, we propose a simple but effective mask mechanism that helps reduce the noise influence in time series and decrease the redundancy of the proposed FMLA by masking some positions of each given series proportionally. To stabilize this mechanism, samples are forwarded through the model with random mask layers several times and their outputs are aggregated to teach the same model with regular mask layers. We conduct extensive experiments on 85 UCR2018 datasets to compare our algorithm with 11 well-known ones and the results show that our algorithm has comparable performance in terms of top-1 accuracy. We also compare our model with three Transformer-based models with respect to the floating-point operations per second and number of parameters and find that our algorithm achieves significantly better efficiency with lower complexity.
Characterizing and Optimizing End-to-End Systems for Private Inference

In two-party machine learning prediction services, the client’s goal is to query a remote server’s trained machine learning model to perform neural network inference in some application domain. However, sensitive information can be obtained during this process by either the client or the server, leading to potential collection, unauthorized secondary use, and inappropriate access to personal information. These security concerns have given rise to Private Inference (PI), in which both the client’s personal data and the server’s trained model are kept confidential. State-of-the-art PI protocols consist of a pre-processing or offline phase and an online phase that combine several cryptographic primitives: Homomorphic Encryption (HE), Secret Sharing (SS), Garbled Circuits (GC), and Oblivious Transfer (OT). Despite the need and recent performance improvements, PI remains largely arcane today and is too slow for practical use. This paper addresses PI’s shortcomings with a detailed characterization of a standard high-performance protocol to build foundational knowledge and intuition in the systems community. Our characterization pinpoints all sources of inefficiency – compute, communication, and storage. In contrast to prior work, we consider inference request arrival rates rather than studying individual inferences in isolation and we find that the pre-processing phase cannot be ignored and is often incurred online as there is insufficient downtime to hide pre-compute latency. Finally, we leverage insights from our characterization and propose three optimizations to address the storage (Client-Garbler), computation (layer-parallel HE), and communication (wireless slot allocation) overheads. Compared to the state-of-the-art PI protocol, these optimizations provide a total PI speedup of 1.8 × with the ability to sustain inference requests up to a 2.24 × greater rate. Looking ahead, we conclude our paper with an analysis of future research innovations and their effects and improvements on PI latency.
Estimating Emotion Contagion on Social Media via Localized Diffusion in Dynamic Graphs

We present a computational approach for estimating emotion contagion on social media networks. Built on a foundation of psychology literature, our approach estimates the degree to which the perceivers' emotional states (positive or negative) start to match those of the expressors, based on the latter's content. We use a combination of deep learning and social network analysis to model emotion contagion as a diffusion process in dynamic social network graphs, taking into consideration key aspects like causality, homophily, and interference. We evaluate our approach on user behavior data obtained from a popular social media platform for sharing short videos. We analyze the behavior of 48 users over a span of 8 weeks (over 200k audio-visual short posts analyzed) and estimate how contagious the users with whom they engage with are on social media. As per the theory of diffusion, we account for the videos a user watches during this time (inflow) and the daily engagements; liking, sharing, downloading or creating new videos (outflow) to estimate contagion. To validate our approach and analysis, we obtain human feedback on these 48 social media platform users with an online study by collecting responses of about 150 participants. We report users who interact with more number of creators on the platform are 12% less prone to contagion, and those who consume more content of `negative' sentiment are 23% more prone to contagion. We will publicly release our code upon acceptance.
Large-Area Intercalated 2D-Pb/Graphene Heterostructure as a Platform for Generating Spin-Orbit Torque

A scalable platform to synthesize ultrathin heavy metals may enable high efficiency charge-to-spin conversion for next-generation spintronics. Here we report centimeter-scale synthesis of air-stable, epitaxially registered monolayer Pb underneath bilayer graphene on SiC (0001) by confinement heteroepitaxy (CHet). Diffraction, spectroscopy, and microscopy reveal CHet-based Pb intercalation predominantly exhibits a mottled hexagonal superstructure due to an ordered network of Frenkel-Kontorova-like domain walls. The system's air stability enables ex-situ spin torque ferromagnetic resonance (ST-FMR) measurements that demonstrate charge-to-spin conversion in graphene/Pb/ferromagnet heterostructures with a 1.5x increase in the effective field ratio compared to control samples.
PASS: A Parameter Audit-Based Secure and Fair Federated Learning Scheme Against Free-Rider Attack

Federated learning (FL) as a secure distributed learning framework gains interests in Internet of Things (IoT) due to its capability of protecting the privacy of participant data. However, traditional FL systems are vulnerable to free-rider (FR) attacks, which causes unfairness, privacy leakage and inferior performance to FL systems. The prior defense mechanisms against FR attacks assumed that malicious clients (namely, adversaries) declare less than 50% of the total amount of clients. Moreover, they aimed for anonymous FR (AFR) attacks and lost effectiveness in resisting selfish FR (SFR) attacks. In this article, we propose a parameter audit-based secure and fair FL scheme (PASS) against FR attack. PASS has the following key features: 1) prevent from privacy leakage with less accuracy loss; 2) be effective in countering both AFR and SFR attacks; and 3) work well no matter whether AFR and SFR adversaries occupy the majority of clients or not. Extensive experimental results validate that PASS: 1) has the same level as the state-of-the-art method in mean square error against privacy leakage; 2) defends against AFR and SFR attacks in terms of a higher defense success rate, lower false positive rate, and higher F1-score; and 3) is still effective where adversaries exceed 50%, with F1-score 89% against AFR attack and F1-score 87% against SFR attack. Note that PASS produces no negative effect on FL accuracy when there is no FR adversary.