In vitro and ex vivo measurement of the biophysical properties of blood using microfluidic platforms and animal models

Haemorheologically impaired microcirculation, such as blood clotting or abnormal blood flow, causes interrupted blood flows in vascular networks. The biophysical properties of blood, including blood viscosity, blood viscoelasticity, haematocrit, red blood bell (RBC) aggregation, erythrocyte sedimentation rate and RBC deformability, have been used to monitor haematological diseases. In this review, we summarise several techniques for measuring haemorheological properties, such as blood viscosity, RBC deformability and RBC aggregation, using in vitro microfluidic platforms. Several methodologies for the measurement of haemorheological properties with the assistance of an extracorporeal rat bypass loop are also presented. We briefly discuss several emerging technologies for continuous, long-term, multiple measurements of haemorheological properties under in vitro or ex vivo conditions.11Ysciescopu

Real-time detection of an airborne microorganism using inertial impaction and mini-fluorescent microscopy

To achieve successful real-time detection of airborne pathogenic microorganisms, the problem must be considered in terms of their physical size and biological characteristics. We developed an airborne microorganism detection chip to realize the detection of microorganisms, ensuring compactness, sensitivity, cost-efficiency, and portability, using three key components: an inertial impaction system, a cartridge-type impaction plate, and a mini-fluorescent microscope. The inertial impaction system was used to separate microorganisms in terms of their aerodynamic particle size, and was fabricated with three impaction stages. Numerical analysis was performed to design the system; the calculated cutoff diameter at each impaction stage was 2.02 (first stage), 0.88 (second stage), and 0.54 μm (third stage). The measured cutoff diameters were 2.24, 0.91, and 0.49 μm, respectively. A cartridge-type impaction plate was used, composed of molded polydimethylsiloxane (PDMS) and an actual impaction region made of a SYBR green I dye-stained agar plate. A mini-fluorescent microscope was used to distinguish microbes from non-biological particles. Images of the microorganisms deposited at the impaction zone were obtained via mini-fluorescent microscopy, and fluorescent intensities of the images were calculated using in-house image-processing software. The results showed that the developed system successfully identified aerosolized biological particles from non-biological particles in real time

Metal work-function-dependent barrier height of Ni contacts with metal-embedded nanoparticles to 4H-SiC

Metal, typically gold [Au], nanoparticles [NPs] embedded in a capping metal contact layer onto silicon carbide [SiC] are considered to have practical applications in changing the barrier height of the original contacts. Here, we demonstrate the use of silver [Ag] NPs to effectively lower the barrier height of the electrical contacts to 4H-SiC. It has been shown that the barrier height of the fabricated SiC diode structures (Ni with embedded Ag-NPs) has significantly reduced by 0.11 eV and 0.18 eV with respect to the samples with Au-NPs and the reference samples, respectively. The experimental results have also been compared with both an analytic model based on Tung's theory and physics-based two-dimensional numerical simulations

Prompt-Augmented Linear Probing: Scaling Beyond The Limit of Few-shot In-Context Learners

Through in-context learning (ICL), large-scale language models are effective few-shot learners without additional model fine-tuning. However, the ICL performance does not scale well with the number of available training samples as it is limited by the inherent input length constraint of the underlying language model. Meanwhile, many studies have revealed that language models are also powerful feature extractors, allowing them to be utilized in a black-box manner and enabling the linear probing paradigm, where lightweight discriminators are trained on top of the pre-extracted input representations. This paper proposes prompt-augmented linear probing (PALP), a hybrid of linear probing and ICL, which leverages the best of both worlds. PALP inherits the scalability of linear probing and the capability of enforcing language models to derive more meaningful representations via tailoring input into a more conceivable form. Throughout in-depth investigations on various datasets, we verified that PALP significantly enhances the input representations closing the gap between ICL in the data-hungry scenario and fine-tuning in the data-abundant scenario with little training overhead, potentially making PALP a strong alternative in a black-box scenario.Comment: AAAI 202

Universal Domain Adaptation for Robust Handling of Distributional Shifts in NLP

When deploying machine learning systems to the wild, it is highly desirable for them to effectively leverage prior knowledge to the unfamiliar domain while also firing alarms to anomalous inputs. In order to address these requirements, Universal Domain Adaptation (UniDA) has emerged as a novel research area in computer vision, focusing on achieving both adaptation ability and robustness (i.e., the ability to detect out-of-distribution samples). While UniDA has led significant progress in computer vision, its application on language input still needs to be explored despite its feasibility. In this paper, we propose a comprehensive benchmark for natural language that offers thorough viewpoints of the model's generalizability and robustness. Our benchmark encompasses multiple datasets with varying difficulty levels and characteristics, including temporal shifts and diverse domains. On top of our testbed, we validate existing UniDA methods from computer vision and state-of-the-art domain adaptation techniques from NLP literature, yielding valuable findings: We observe that UniDA methods originally designed for image input can be effectively transferred to the natural language domain while also underscoring the effect of adaptation difficulty in determining the model's performance.Comment: Findings of EMNLP 202

Probing Out-of-Distribution Robustness of Language Models with Parameter-Efficient Transfer Learning

As the size of the pre-trained language model (PLM) continues to increase, numerous parameter-efficient transfer learning methods have been proposed recently to compensate for the tremendous cost of fine-tuning. Despite the impressive results achieved by large pre-trained language models (PLMs) and various parameter-efficient transfer learning (PETL) methods on sundry benchmarks, it remains unclear if they can handle inputs that have been distributionally shifted effectively. In this study, we systematically explore how the ability to detect out-of-distribution (OOD) changes as the size of the PLM grows or the transfer methods are altered. Specifically, we evaluated various PETL techniques, including fine-tuning, Adapter, LoRA, and prefix-tuning, on three different intention classification tasks, each utilizing various language models with different scales.Comment: *SEM 202

Characterizing Natural User Interface with Wearable Smart Watches

Background - The emergence of new interaction paradigms makes the use of technology inrealizing the users??? natural ways of exploring the real world the ultimate goal of designers today.Research on interactive and immersive technologies for user interface design is still a challenging chore for engineers and scientists when it comes to designing natural interaction for wearable smart devices. To address the challenge, our study aims to develop guidelines for design practitioners in designing wearable smart watches that could offer natural user experiences. Methods - To better understand natural user experiences with smart watches, an extensive literature review was conducted. A quantitative survey with 80 participants was conducted, of which the focus was on the expected functions of smart watches. Based on the survey results, we selected eight participants in terms of technology familiarity. To achieve the objectives of our research, three studies were conducted: a design workshop (Study 1), a cultural probe (Study 2), and a focus group interview (Study 3). The design workshop was created to figure out the needs and wishes people have forsmart watches. In the cultural probe, the focus was on figuring out natural interactions with smart watches. Finally, the focus group interview aimed to gain more insights from the results of the cultural probe in terms of natural user interaction with particular functions. Results - To address the needs and wishes of the users toward wearable smartwatches, we made a subdivision into three categories, such as functions, input measures, and notification (feedback) methods. According to the results, participants wanted weather notification, health monitoring, and identification as expected functions. Regarding the methodof input, voice command and touch screen were preferred. In order to get feedback, most of the participantswanted vibrations, particularly as a reaction tocompleting the commands or inputs. There was also a suggestion to customize their smart watch. For example, users can select the functions and build their own command system, and even choose the notificationmethods. Considering natural user interface with respect to functions (weather, answering a call, navigation, health monitoring, taking a picture and messaging), specific natural user interfaces were mentioned for particular functions. Conclusions - Throughout the study, people???s needs and wishes and their perceptions about natural interaction were identified and the characteristics of natural user interfacesweredetermined. Based on the results, tenperceptions were specifically defined to provide a better understanding of smart watches in terms of natural interaction: user affinity of form, awareness by familiarity, reality correspondence, behavioral extension, purpose orientation, easiness of performance, timeliness, routine acceptance, generality, and rule of thumb. In addition to that, natural user interfaces were categorized into five groups: user familiarity, realistic interaction, accomplishment assistance, contextual appropriateness, and social awareness. In this study,we tried to identify what constitutes anatural interaction and how it should be created. The limitations and further study are discussed at the end.ope

Time-resolved pathogenic gene expression analysis of the plant pathogen Xanthomonas oryzae pv. oryzae

Virulence of wild-type and mutant Xoo strains on rice. (DOCX 16 kb