Miracle-dz/UniFAR-FTUs huggingface dataset:
Allied Interpreters: Exploring the Role Perception and Ethics of Uncertified Interpreters Supporting Migrant Agricultural Workers in British Columbia

Uncertified interpreters enable migrant agricultural workers in Canada’s Seasonal Agricultural Worker Program to access key resources and connect with community. Through providing a range of services, including support work and advocacy, interpreters assist migrant workers at risk of exploitation and injury in Canada. This article explores how uncertified interpreters navigate the power dynamics between migrant workers, interpreters, and other actors. Moreover, this article investigates how uncertified interpreters perceive their role and the ethical values that guide their communicative methods. This study’s research findings show that interpreters may adopt a pro-worker role perception as they gain knowledge of the disempowerment experienced by migrant workers. Arising from this role perception, interpreters may also adopt pro-worker ethical values that renounce interpreter neutrality in favour of accessibility and an explanatory communication style. Ultimately, this article contends that uncertified interpreters may reject some traditional interpretation guidelines to adopt a role perception, ethical framework, and communicative style perceived to be more well-suited to supporting migrant farm workers in British Columbia.
LGBTQ in Youth: A Narrative Review

Lesbian, gay, bisexual, transgender and queer/questioning youth have experienced stigma in the form of stressors including rejection by parents and peers, discrimination, harassment and violence. The prevalence has ranged from 18% to 67% in different samples. The disparities they have experienced include sexual and mental health, substance use and suicide risk. Since they spend much of their time in school, gay straight alliances have been created and have helped reduce these problems. Despite the limitations of this recent literature, the research highlights the ongoing problems of LGBTQ youth and the need for continuing research and interventions. This narrative review involved entering the terms LGBTQ and youth into PubMed and PsycINFO. The search yielded 541 papers for the last five years. However, following exclusion criteria including case studies and non-English papers, this review is a summary of the research reported in 66 papers. The recent literature on LGBTQ and youth is predominantly focused on negative effects of belonging to a sexual or gender minority group along with some studies on comorbidities, buffers and interventions. This narrative review is accordingly divided into sections on prevalence, effects/ correlates, comorbidities, buffers and interventions.
Cosmological Constant in LQG Vertex Amplitude

A new q-deformation of the Euclidean EPRL/FK vertex amplitude is proposed by using the evaluation of the Vassiliev invariant associated with a 4-simplex graph (related to two copies of quantum SU(2) group at different roots of unity) embedded in a 3-sphere. We show that the large-j asymptotics of the q-deformed vertex amplitude gives the Regge action with a cosmological constant. In the end we also discuss its relation with a Chern-Simons theory on the boundary of 4-simplex.
Energy Efficient End Device Aware Solution Through SDN in Edge-Cloud Platform

Recently, the networking industries have gone through tremendous changes. It demands high-speed operations and complex problem-solving abilities. To manage these evolutions Internet-of-Things (IoT) is a proposed solution from several technical corners. Numerous researchers and government organizations showing their interest to provide solutions with IoT implementation. Handling a huge amount of network data, its privacy and security, Quality of Service (QoS) requirements and heterogeneity of underlying networking components are the various challenges in IoT implementations. To provide the solution, Software Defined Networking (SDN) is becoming a bliss in managing such complex networking problems. The allocation of the Virtual Machines (VMs) into the end device is an NP-Hard combinatorial optimization problem. We formulate the problem by using simple Additive Weighing (SAW) or Weighted Sum Method (WSM) to allocate the VMs asymmetrically based on CPU Utilization and Memory usage to optimize the energy. The proposed algorithm ServerCons minimizes the number of live migrations and the number of nodes used as well as the energy usage is at par with the state of art algorithms such as First-Fit-Decreasing(FFD), Best-Fit-Decreasing (BFD), and Modified-Best-Fit-Decreasing (MBFD).
Effects of developmental stage and store time on the microbial community and fermentation quality of sweet sorghum silage

Abstract This study investigated the effects of developmental stage and store time on the chemical composition, microbial community, co-occurrence networks and fermentation characteristics of sweet sorghum silage. Sweet sorghum harvested at two developmental stages (heading stage, S1; hard dough stage, S2) was treated as follows: (I) natural fermentation of S1 (NS1); (II) natural fermentation of S2 (NS2) and ensiled for 1, 3, 7, 15, 30 and 60 days. After 60 days of ensiling, NS2 silage had higher lactic acid concentration and the ratio of lactic to acetic acid, and lower pH value and acetic acid concentration than NS1 silage. Meanwhile, NS2 silage also had higher ammonia nitrogen (NH3-N) content than NS1 silage, but the NH3-N content of both treatments was lower than 100 g/kg TN. Leuconostoc and Lactococcus were respectively dominant in both 7-day NS1 and NS2 silages, while Lactobacillus was the most abundant genus in 30-day NS1 and NS2 silages. The developmental stage altered the bacterial co-occurrence networks of fresh and ensiled sweet sorghum. Spearman’s correlation heatmap showed that the higher lactic acid content and ratio of lactic to acetic acid in NS2 silage could be associated with the higher water-soluble carbohydrate content in S2 material, the higher abundance of Lactococcus in the initial phase of ensiling and the higher abundance of Lactobacillus in the late phase of ensiling. These results concluded that the sweet sorghum harvested at the hard dough stage is preferred for silage production over the sweet sorghum harvested at the heading stage. HIGHLIGHTS Microbial succession pattern was studied on fresh and ensiled samples. Growth stage affected the chemical and microbial parameters of sweet sorghum. Epiphytic microbiota was correlated with the chemical composition of forage. Metagenomic sequencing showed Lactobacillus was dominated in all silages. Growth stage accelerated the fermentation of sweet sorghum silage.
Cyclotron resonance study of the electron and hole velocity in graphene monolayers

We report studies of cyclotron resonance in monolayer graphene. Cyclotron resonance is detected using the photoconductive response of the sample for several different Landau level occupancies. The experiments measure an electron velocity at the K- (Dirac) point of $c_{K}^{*}$ = 1.093 x 10$^{6}$ ms$^{-1}$ and in addition detect a significant asymmetry between the electron and hole bands, leading to a difference in the electron and hole velocities of 5% by energies of 125 meV away from the Dirac point.
Chatting with AI Chatbots Applications to Improve English Communication Skill

Artificial intelligence allows a person to converse with machines, computers or robots. Chatbots are an application that you can talk to like you would talk to a human. Chatbots can be a tool to practice the language learned anywhere and anytime. In order to improve students' communication skills in English, researchers conducted research on the use of artificial intelligence Chatbots applications in learning English courses in the PKh Department for the 2020/2021 academic year. This study uses a descriptive method to describe the process of learning English with chatbots and to determine student perceptions of the use of these chatbots in improving their communication skills in English. After having conversations with chatbots: ELIZA, ALICE, MITSUKU/KUKI, and ANDY with conversation topics: introductions, feelings/confessions, daily activities, hobbies, lectures, COVID-19 pandemic, etc. The results obtained are the most preferred Chatbots: ANDY, there are POSITIVE meaningful expressions (86%) and no NEGATIVE meanings towards ANDY chatbot. Least favorite chatbots: ELIZA, there are a lot of NEGATIVE (43%) meaningful expressions towards ELIZA chatbot which are bigger than POSITIVE expressions (39%). © 2022 JELS and the Authors - Published by JELS.
Dynamic Graph Neural Network Learning for Temporal Omics Data Prediction

High-throughput studies of biological systems are rapidly generating a wealth of ‘omics’-scale data. Many of these studies are temporal collecting proteomics and genomics data capturing dynamic observations. While temporal omics data are essential to unravel the mechanisms of various diseases, they often include missing (or incomplete) values due to technical and experimental reasons. Data prediction methods, i.e., imputation and forecasting, have been widely used to mitigate these issues. However, existing imputation and forecasting techniques typically address static omics data representing a single time point and perform forecasting on data with complete values. In this paper, we propose a graph-based method for temporal omics data imputation and forecasting that handle omics data containing missing values at multiple time points. The method takes advantage of topological relationships (e.g., protein-protein and gene-gene interactions) among omics data samples and incorporates a graph convolutional network to first infer the missing values at different time points. Then, we combine these inferred values with the original omics data to perform temporal imputation and forecasting using a long short-term memory network. Evaluating the proposed method on two real-world datasets demonstrated a distinct advantage over existing data imputation and forecasting methods. On the omics dataset, the average mean square error of our method improved 11.3% for imputation and 6.4% for forecasting compared to the baseline methods.
Optical Distribution Network Design Using PSO

Fiber To The Home (FTTH) network based on the Gigabit Passive Optical Network (GPON) technology is considered a technology option capable of spreading high-speed Internet. However, the high project cost may make its deployment unfeasible. Given this challenge, we use Particle Swarm Optimization (PSO) to propose an Optical Distribution Network (ODN) design in FTTH network. The ODN is a region that links the Central Office (CO) and the User Network (UN), that is, a strategic region that needs additional attention. In the literature so far is rare to find a technical-economic analysis of the ODN problem. Therefore, the novelty of this letter is to adapt the PSO, an efficient and fast strategy to be applied to multivariable functions, within an ODN design with technical and economic criteria. Using system-level simulations, we attest that the proposed algorithm achieves 12% cost reduction from the conventional way.
Non-Locality Distillation is Impossible for Isotropic Quantum Systems

Non-locality is a powerful resource for various communication and information theoretic tasks, e.g., to establish a secret key between two parties, or to reduce the communication complexity of distributed computing. Typically, the more non-local a system is, the more useful it is as a resource for such tasks. We address the issue of non-locality distillation, i.e., whether it is possible to create a strongly non-local system by local operations on several weakly non-local ones. More specifically, we consider a setting where non-local systems can be realized via measurements on underlying shared quantum states. The hardest instances for non-locality distillation are the isotropic quantum systems: if a certain isotropic system can be distilled, then all systems of the same non-locality can be distilled as well. The main result of this paper is that non-locality cannot be distilled from such isotropic quantum systems. Our results are based on the theory of cross norms defined over the tensor product of certain Banach spaces. In particular, we introduce a single-parameter family of cross norms, which is used to construct a hierarchy of convex sets that are closed under local operations. This hierarchy interpolates between the set of local systems and an approximation to the set of quantum systems.
State-of-the-art techniques for promoting tissue regeneration: Combination of three-dimensional bioprinting and carbon nanomaterials

181Biofabrication approaches, such as three-dimensional (3D) bioprinting of hydrogels, have recently garnered increasing attention, especially in the construction of 3D structures that mimic the complexity of tissues and organs with the capacity for cytocompatibility and post-printing cellular development. However, some printed gels show poor stability and maintain less shape fidelity if parameters such as polymer nature, viscosity, shear-thinning behavior, and crosslinking are affected. Therefore, researchers have incorporated various nanomaterials as bioactive fillers into polymeric hydrogels to address these limitations. Carbon-family nanomaterials (CFNs), hydroxyapatites, nanosilicates, and strontium carbonates have been incorporated into printed gels for application in various biomedical fields. In this review, following the compilation of research publications on CFNs-containing printable gels in various tissue engineering applications, we discuss the types of bioprinters, the prerequisites of bioink and biomaterial ink, as well as the progress and challenges of CFNs-containing printable gels in this field.
MOFs and MOF-Derived Materials for Antibacterial Application

Bacterial infections pose a serious threat to people’s health. Efforts are being made to develop antibacterial agents that can inhibit bacterial growth, prevent biofilm formation, and kill bacteria. In recent years, materials based on metal organic frameworks (MOFs) have attracted significant attention for various antibacterial applications due to their high specific surface area, high enzyme-like activity, and continuous release of metal ions. This paper reviews the recent progress of MOFs as antibacterial agents, focusing on preparation methods, fundamental antibacterial mechanisms, and strategies to enhance their antibacterial effects. Finally, several prospects related to MOFs for antibacterial application are proposed, aiming to provide possible research directions in this field.
Fermi edge resonances in non-equilibrium states of Fermi gases

We formulate the problem of the Fermi edge singularity in non-equilibrium states of a Fermi gas as a matrix Riemann–Hilbert problem with an integrable kernel. This formulation is the most suitable for studying the singular behavior at each edge of non-equilibrium Fermi states by means of the method of steepest descent, and also reveals the integrable structure of the problem. We supplement this result by extending the familiar approach to the problem of the Fermi edge singularity via the bosonic representation of the electronic operators to non-equilibrium settings. It provides a compact way to extract the leading asymptotes.
Ability of combined soluble urokinase plasminogen activator receptor to predict preventable emergency attendance in older patients in Japan: a prospective pilot study

Soluble urokinase plasminogen activator receptor (suPAR) is a strong and nonspecific inflammatory biomarker that reflects various immunologic reactions, organ damage, and risk of mortality in the general population. Although prior research in acute medical patients showed that an elevation in suPAR is related to intensive care unit admission and risk of readmission and mortality, no studies have focused on the predictive value of suPAR for preventable emergency attendance (PEA). This study aims to evaluate the predictive value of suPAR, which consists of a combination of white blood cell count (WBC), C-reactive protein (CRP), and the National Early Warning Score (NEWS), for PEA in older patients (>65 years) without trauma who presented to the emergency department (ED). This single-center prospective pilot study was conducted in the ED of the Association of EISEIKAI Medical and Healthcare Corporation Minamitama Hospital, in Hachiouji City, Tokyo, Japan, from September 16, 2020, to June 21, 2022. The study included all patients without trauma aged 65 years or older who were living in their home or a facility and presented to the ED when medical professionals decided an emergency consultation was required. Discrimination was assessed by plotting the receiver-operating characteristic (ROC) curve and calculating the area under the ROC curve (AUC). During the study period, 49 eligible older patients were included, and thirteen (26.5%) PEA cases were detected. The median suPAR was significantly lower in the PEA group than in the non-PEA group (p < 0.05). For suPAR, the AUC for the prediction of PEA was 0.678 (95% CI 0.499–0.842, p < 0.05), and there was no significant difference from other variables as follows: 0.801 (95% CI 0.673–0.906, p < 0.001) for WBC, 0.833 (95% CI 0.717–0.934, p < 0.001) for CRP, and 0.693 (95% CI 0.495–0.862, p < 0.05) for NEWS. Furthermore, the AUC for predicting PEA was 0.867 (95% CI 0.741–0.959, p < 0.001) for suPAR + WBC + CRP + NEWS, which was significantly higher than that of the original suPAR (p < 0.01). The cutoff values, sensitivity, specificity, and odds ratio of suPAR and suPAR + WBC + CRP + NEWS were 7.5 and 22.88, 80.6% and 83.3%, 53.8% and 76.9%, and 4.83 and 16.67, respectively. This study has several limitations. First, this was pilot study, and we included a small number of older patients. Second, the COVID-19 pandemic occurred during the study period, so that there may be selection bias in the study population. Third, our hospital is a secondary emergency medical institution, and as such, we did not treat very fatal cases, which could be another cause of selection bias. Our single-center study has demonstrated the moderate utility of the combined suPAR as a triage tool for predicting PEA in older patients without trauma receiving home medical care. Before introducing suPAR to the prehospital setting, evidence from multicenter studies is needed.
Algebraic Kasparov K-theory, II

This paper is to construct unstable, Morita stable and stable bivariant algebraic Kasparov $K$-theory spectra of $k$-algebras. These are shown to be homotopy invariant, excisive in each variable $K$-theories. We prove that the spectra represent universal unstable, Morita stable and stable bivariant homology theories respectively.
Control Mechanisms and Senior Management Commitment in Shaping the Performance of Strategic Information Systems Projects: A Resource Dependence Perspective

Successfully controlling strategic information systems (IS) projects in realizing strategic goals is a primary concern for managers. However, the effectiveness of control may vary with the organizational resources, such as senior management commitment. Using a theoretical lens of resource dependence, this article investigates the mechanism of how senior management commitment, a critical organizational resource, changes the influences of four types of control on the performance of strategic IS projects. Based on a pairwise survey on user liaisons and project managers from 155 strategic IS projects, we discover that behavior control and self-control are effective in improving strategic performance contrary to outcome and clan control. However, such effects are differentially changed by senior management commitment, which increases the effectiveness of outcome and clan control but weakens that of self-control. Thus, senior management commitment has dual roles toward strategic performance in either facilitating or deteriorating control effectiveness. Our findings contribute to control-based theory, resource dependence theory, strategic IS project, and management commitment literature by identifying the interactive effect of senior management commitment and control. Our findings also provide practical insights into how managers substantially control and support strategic IS projects.
Nonassociative geometry and twist deformations in non-geometric string theory

We describe nonassociative deformations of geometry probed by closed strings in non-geometric flux compactifications of string theory. We show that these non-geometric backgrounds can be geometrised through the dynamics of open membranes whose boundaries propagate in the phase space of the target space compactification, equiped with a twisted Poisson structure. The effective membrane target space is determined by the standard Courant algebroid over the target space twisted by an abelian gerbe in momentum space. Quantization of the membrane sigma-model leads to a proper quantization of the non-geometric background, which we relate to Kontsevich's formalism of global deformation quantization that constructs a noncommutative nonassociative star product on phase space. We construct Seiberg-Witten type maps between associative and nonassociative backgrounds, and show how they may realise a nonassociative deformation of gravity. We also explain how this approach is related to the quantization of certain Lie 2-algebras canonically associated to the twisted Courant algebroid, and cochain twist quantization using suitable quasi-Hopf algebras of symmetries in the phase space description of R-space which constructs a Drinfel'd twist with non-trivial 3-cocycle. We illustrate and apply our formalism to present a consistent phase space formulation of nonassociative quantum mechanics.
Modeling the Human Sinoatrial Node Based on Sequential Discharge Hypothesis

The electrical synchronization of human sinoatrial (SA) node cells for propagating the pacemaker activity has always been an important challenge in literatures. Nevertheless, most literatures, that provide hypotheses for the electrical synchronization of SA node cells, only investigated the activity of a very small group of coupled SA node cells. Therefore, this study proposes a novel SA node model based on the sequential discharge hypothesis to estimate the electrical potential around the SA node, which electrodes measure it. This model consists of a three-dimensional regular network of Hodgkin-Huxley (HH) model modified by time constant n  that propagates the action potentials of dominant pacemaker through the gap junctions. The results show that the HH model modified in this study not only has adequate capacity for generating oscillations between 40 and 180 beats per minute (BPM), but also their three-dimensional regular network can provide a suitable estimate from the electrical potential around the SA node. Therefore, this model is a good suggestion for the electrical synchronization of large mammalian SA node cells, especially
Multiobjective Model-Free Predictive Control for Motor Drives and Grid-Connected Applications: Operating With Unbalanced Multilevel Cascaded H-Bridge Inverters

A multiobjective model-free predictive control (MO-MFPC) strategy is proposed in this article for multilevel cascaded H-bridge (MLCHB) inverters with unbalanced conditions. The compensated current variation (CCV), which allows the inclusion of the proportional and integral terms into the cost function, is generalized to improve the accuracy of MFPC over a wide range of applications. The new extended CCV is used to define the voltage control objective without involving the output voltage model of MLCHB. This voltage control objective is used to evaluate all state candidates to achieve a suitable subset for the current control objective. To achieve a better tradeoff between the current accuracy and the injected common-mode voltage (CMV), CMV is added to the cost function. Simulations and experimental evaluations show that, compared to existing MFPCs and classic model predictive control for MLCHB inverters, MO-MFPC achieves a better current accuracy over a wide range of applications and unbalanced MLCHB operating conditions.