Scaling Of Dimensions Research Articles

A Case Report on Functional Dyspepsia Treated with Korean Medicine in a Patient with Panic Disorder and Lower Back Pain

Objectives: This study reports on the efficacy of Korean medical treatments for a functional dyspepsia patient with panic disorder and lower back pain.Methods: A 51-year-old male patient with functional dyspepsia was treated with herbal medicines and acupuncture for 17 days. The treatment effect was evaluated by measurements drawn from the Numerical Rating Scale, range of motion, Oswestry Disability Index, European Quality of Life 5 Dimensions Scale, and Gastrointestinal Symptom Score.Results: Following the treatment, the patient showed a decrease on the Numerical Rating Scale and Oswestry Disability Index and in Gastrointestinal Symptom Score, as well as an improvement in range of motion and European Quality of Life 5 Dimensions score.Conclusions: Korean medical treatments appear to be effective in reducing functional dyspepsia. Further clinical research on patients with functional dyspepsia is needed.

A Case Report of Suspected Allergic Rhinitis in a Patient with LBP Hospitalized at a Korean Medicine Hospital and Treated with Korean Medicine

Objective: The purpose of this study is to report the efficacy of using Korean medical treatment for suspected allergic rhinitis.Methods: We used Korean medical treatments (herbal medicines and acupuncture) to treat a hospitalized patient with suspected allergic rhinitis. To evaluate the treatment, we used Total Nasal Symptom Scores to measure sneezing, rhinorrhea, itching, and obstruction. The degree of rhinitis was also evaluated using the Visual Analogue Scale, and the patient’s generic health status was measured using the European Quality of Life 5 Dimensions Scale.Results: Visual Analogue Scale and European Quality of Life 5 Dimensions Scale scores improved after treatment. The change in Total Nasal Symptom Scores showed that the patient’s suspected allergic rhinitis symptoms were relieved.Conclusions: The results of this study suggest that Korean medicine therapies may be effective for treating suspected allergic rhinitis.

A Case Report of Korean Medical Treatment of a Dyspepsia Patient with Lethargy and Dizziness

Objectives: The aim of this case report was to present the effects of Korean medicine treatment on a patient with dyspepsia symptoms like those of gastroesophageal reflux disease.Methods: A 64-year-old male patient with dyspepsia was treated with <i>Sosiho-tang</i> decoction, <i>Banhasasim-tang</i> soft extract, <i>Gamihyangsayukgunja-tang</i> decoction, and Kracie <i>Sihogayonggolmoryu-tang</i> extract, along with acupuncture, pharmacopuncture, and deep tissue meridian hot pack therapy for five days of hospitalization. Pain from the dyspepsia was assessed using the Numerical Rating Scale and the European Quality of Life 5 Dimensions Scale.Results: Within five days of treatment, dyspepsia was relieved from a Numerical Rating Scale score of 7 to a score of 3. The European Quality of Life 5 Dimensions Scale score increased from 0.455 to 0.816.Conclusion: These results show that dyspepsia can be relieved with Korean medicine treatment. However, further well-designed studies are required to confirm these findings.

Scaling of Chinese urban CO2 emissions and multiple dimensions of city size

Cities are both the primary cause of global climate change and the key to the mitigation agenda. China's unprecedented urbanization has paralleled a growth in energy demand and urban areas have emerged as the crux of CO2 emissions reduction in China. There is a crucial need for policymakers to understand how CO2 emissions scale with city size and adopt economies of scale (cost savings) for mitigation, particularly through a multidimensional lens of city size. This study reveals a set of scaling relations between urban scope 1 CO2 emissions and five dimensions of city size in 340 Chinese cities, including population (POP), built-up area (BA), building height (BH), specific built-up area (SBA), and built-up volume (BV). The findings show that CO2 emissions in Chinese cities scale linearly with POP and BA but sublinearly with BA, SBA, and BV, and more diverse regimes exist across various geographic zones, population hierarchies, administrative hierarchies, and governance contexts. The prevalent sublinear scaling regime between CO2 emissions and SBA and BV demonstrates the potential importance of optimizing the vertical built-up landscapes for establishing a zero‑carbon society. Furthermore, the top 10 % and bottom 10 % performance of individual cities in emissions identified by the Scale-Adjusted Metropolitan Indicator (SAMI) (the smaller the better) highlights the imprints of the socioeconomic context (e.g., Low Carbon City Initiative) on the scaling of CO2 emissions in Chinese cities, which is critical for developing decarbonization strategies. Our multidimensional analysis can assist in the local-tailored low-carbon development of Chinese cities.

(Invited) Nm-Scale Patterns and Selectivity: A Blessing or a Curse

Area-selective deposition (ASD) is a promising technique for semiconductor device manufacturing. The replication of nanoscale patterns by ASD can simplify device fabrication process flows by reducing the number of lithography, etch and chemical-mechanical polishing steps. In addition, ASD could eliminate pattern overlay errors. ASD is of special interest as device dimensions scale and has recently been shown as viable approach for the fully self-aligned via, to enable interconnect scaling beyond the 3 nm node [1]. However, the dependence of the selectivity of ALD and CVD processes on the patterning process and pattern dimensions is poorly documented. This aspect will be investigated in the current presentation. We will discuss the fundamental mechanisms of ALD growth mechanisms and how they influence selectivity. Next, we will discuss an example of Ru ASD with defect mitigation in nm-scale patterns on full 300-mm wafers [2].[1] Chen et al., IEDM21, 486-489.[2] Clerix et al., Adv. Mater. Interfaces 2021, 2100846.

Investigation of Transient Two-Stage Thermal Equivalent RC Network of SOI-MOSFETs Using Nano Double-Pulse Measurement

The self-heating effect (SHE) of silicon-on-insulator (SOI) MOSFETs brings challenges to the measurement and modeling of transient electrothermal characteristics. For the first time, this study obtains the transient two-stage thermal equivalent RC network of SOI MOSFETs by nano double-pulse measurement combined with network identification by a deconvolution (NID) method. The two-stage model provides a comprehensive reference for the accumulation of residual heat under dynamic operation. We reveal that since the oxide layer acts as a thermal reservoir, the heat dissipation process can be divided into three phases according to thermal time constants. The results of geometry dependence of thermal parameters show that the gate length and width-to-length ratio ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${W}/{L}$ </tex-math></inline-formula> ) increase: the thermal resistance trend of both stages decreases, the one-stage thermal time constant increases, but the two-stage thermal time constant decreases. Also, as the scaling of device dimension and mutual thermal coupling, the thermal transient response boosts significantly.

Prevalence of pain and its association with quality of life of patients with heart failure in a developing country: findings from a multicenter cross-sectional study

BackgroundHeart failure (HF) is considered one of the main causes of morbidity and death among chronic diseases worldwide. Patients have increasingly reported chronic pain in long-standing heart failure as a disturbing symptom. Its unknown etiology and mechanism, in addition to its insidious progressive nature, made both the doctor and the patient not notice it until it affects the quality of life (QoL) and general health status. The primary objective of this study is to find the prevalence of pain in chronic heart failure patients and its impact on their QoL. The secondary objective is to determine the predictors of QoL in HF patients.MethodsA multicenter cross-sectional design was used. The European Quality of Life scale five dimensions scale and the Brief Pain Inventory were adopted to evaluate QoL and pain, respectively. The Statistical Package for the Social Sciences version 25 was applied to present the data. The Mann-Whitney U, Kruskal-Wallis, and Cronbach alpha tests were used.ResultsThe final study had a total of 142 individuals. The prevalence of pain among HF patients was 84.5%. Knee pain was the main complaint among patients. Our patients' median pain severity score was 18 [5.00–25.00], while the median pain interference score was 39 [24.75–53.00]. They had a median EQ-5D score of 0.34 [0.0–0.6] and an EQ-VAS score of 50 [30–70]. Pain severity (p = 0.004 and p < 0.001, respectively) and pain interference (p < 0.001 and p = 0.001, respectively) were found to significantly associated with both QoL scores; the visual analogue scale (EQ-VAS) and EQ-5D-5L. In multivariate analysis, monthly income was the only variable significantly correlated with EQ-VAS and EQ-5D-5L, along with pain variables.ConclusionsPain is a common symptom among patients with HF and is significantly associated with their QoL. Low income is also highly associated with poor QoL. Definitive guidelines should be achieved to increase awareness and understanding of the importance of pain management, reaching a higher QoL level, less pain, and good adherence to HF medications.

A CMOS compatible thermoelectric device made of crystalline silicon membranes with nanopores

Herein, we report the use of nanostructured crystalline silicon as a thermoelectric material and its integration into thermoelectric devices. The proof-of-concept relies on the partial suppression of lattice thermal conduction by introducing pores with dimensions scaling between the electron mean free path and the phonon mean free path. In other words, we artificially aimed at the well-known ‘electron crystal and phonon glass’ trade-off targeted in thermoelectricity. The devices were fabricated using CMOS-compatible processes and exhibited power generation up to 5.5 mW cm−2 under a temperature difference of 280 K. These numbers demonstrate the capability to power autonomous devices with environmental heat sources using silicon chips of centimeter square dimensions. We also report the possibility of using the developed devices for integrated thermoelectric cooling.

Recent progress on negative capacitance tunnel FET for low-power applications: Device perspective

In the present-day scenario of low-power electronics, there is a steady and increasing need for an adequate device that can counteract the power dissipation issue due to the consistent scaling of device dimensions. For this purpose, the evolution of low subthreshold swing (SS) based devices, especially with the negative capacitance (NC) techniques, has presented a well-favored solution. The NC of ferroelectrics (FE) materials could be widely utilized to provide the gate voltage (VG) amplification under specific conditions to boost the performance of the MOS device, by addressing the ultimate fundamental limitation of Boltzmann Tyranny and offering the SS much lower than 60mV/dec. Along with the advent of this state-of-art NC technology, tunnel field-effect transistor (TFET) also emerges for accomplishing low SS and becomes one of the promising techniques for low-power applications. Incorporating these two principles (NC and tunneling) into a single device architecture enables the super-steep SS and remarkably low OFF current (IOFF). This cutting-edge combination, negative capacitance tunnel FET (NC-TFET) device has opened up the possibility of an ultra-low-power and high-performance device. This review paper mainly focuses on the theoretical background and recent progress in the field of NC-TFET with abundant quantum-mechanical models and various perspectives such as transistor perspective, analog circuit perspective, and future road map perspective.

Experimental Demonstration of Swift Analytical Universal Control Over Nearby Transitions

Along with the scaling of dimensions in quantum systems, transitions between the system's energy levels would become close in frequency, which are conventionally resolved by weak and lengthy pulses. Here, we extend and experimentally demonstrate analytically based swift quantum control techniques on a four-level trapped ion system, where we perform individual or simultaneous control over two pairs of spectrally nearby transitions with tailored time-varied drive, achieving operational fidelities ranging from 99.2(3)% to 99.6(3)%. We achieve approximately an order of magnitude speed up compared with the case of a weak square pulse for a general control. Therefore, our demonstration may be beneficial to a broad range of quantum systems with crowded spectrum, for spectroscopy, quantum information processing, and quantum simulation.

Flow similarity, stochastic branching, and quarter-power scaling in plants.

The origin of allometric scaling patterns that are multiples of one-fourth has long fascinated biologists. While not universal, quarter-power scaling relationships are common and have been described in all major clades. Several models have been advanced to explain the origin of such patterns, but questions regarding the discordance between model predictions and empirical data have limited their widespread acceptance. Notable among these is a fractal branching model that predicts power-law scaling of both metabolism and physical dimensions. While a power law is a useful first approximation to some data sets, nonlinear data compilations suggest the possibility of alternative mechanisms. Here, we show that quarter-power scaling can be derived using only the preservation of volume flow rate and velocity as model constraints. Applying our model to land plants, we show that incorporating biomechanical principles and allowing different parts of plant branching networks to be optimized to serve different functions predicts nonlinearity in allometric relationships and helps explain why interspecific scaling exponents covary along a fractal continuum. We also demonstrate that while branching may be a stochastic process, due to the conservation of volume, data may still be consistent with the expectations for a fractal network when one examines sub-trees within a tree. Data from numerous sources at the level of plant shoots, stems, and petioles show strong agreement with our model predictions. This theoretical framework provides an easily testable alternative to current general models of plant metabolic allometry.

A dual-stage deep convolutional neural network for automatic diagnosis of COVID-19 and pneumonia from chest CT images

In the Coronavirus disease-2019 (COVID-19) pandemic, for fast and accurate diagnosis of a large number of patients, besides traditional methods, automated diagnostic tools are now extremely required. In this paper, a deep convolutional neural network (CNN) based scheme is proposed for automated accurate diagnosis of COVID-19 from lung computed tomography (CT) scan images. First, for the automated segmentation of lung regions in a chest CT scan, a modified CNN architecture, namely SKICU-Net is proposed by incorporating additional skip interconnections in the U-Net model that overcome the loss of information in dimension scaling. Next, an agglomerative hierarchical clustering is deployed to eliminate the CT slices without significant information. Finally, for effective feature extraction and diagnosis of COVID-19 and pneumonia from the segmented lung slices, a modified DenseNet architecture, namely P-DenseCOVNet is designed where parallel convolutional paths are introduced on top of the conventional DenseNet model for getting better performance through overcoming the loss of positional arguments. Outstanding performances have been achieved with an F1 score of 0.97 in the segmentation task along with an accuracy of 87.5% in diagnosing COVID-19, common pneumonia, and normal cases. Significant experimental results and comparison with other studies show that the proposed scheme provides very satisfactory performances and can serve as an effective diagnostic tool in the current pandemic.

Modeling of Classical Channel Hot Electron Degradation in n-MOSFETs Using TCAD

A technology CAD (TCAD) setup is used to calculate the channel hot electron (CHE) induced parametric drift in n-MOSFETs. The setup uses reaction-diffusion-drift model and utilizes carrier energy, vertical electric field, and lattice temperature effects, to calculate the time kinetics of trap generation and its impact on the device parametric drift. Experimental data from published reports, measured using different probes, for midgate bias stress under varying drain bias ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\sim 3$ </tex-math></inline-formula> –8 V) and temperature (0 °C–100 °C) are modeled, in classical devices having different channel lengths (2.0– <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$0.3~\mu \text{m}$ </tex-math></inline-formula> ) and oxide thicknesses (35–5 nm). The impact of device dimension scaling on the spatial distribution of generated traps and their impact on the device parametric drift are discussed.

Aprendizaje para la optimización con Savant Virtual

Optimization problems arising in multiple fields of study demand efficient algorithms that can exploit modern parallel computing platforms. The remarkable development of machine learning offers an opportunity to incorporate learning into optimization algorithms to efficiently solve large and complex problems. This article explores Virtual Savant, a paradigm that combines machine learning and parallel computing to solve optimization problems. Virtual Savant is inspired in the Savant Syndrome, a mental condition where patients excel at a specific ability far above the average. In analogy to the Savant Syndrome, Virtual Savant extracts patterns from previously-solved instances to learn how to solve a given problem in a massively-parallel fashion. In this article, Virtual Savant is applied to three optimization problems related to software engineering, task scheduling, and public transportation. The efficacy of Virtual Savant is evaluated in different computing platforms and the experimental results are compared against exact and approximate solutions for both synthetic and realistic instances of the studied problems. Results show that Virtual Savant can find accurate solutions, effectively scale in the problem dimension, and take advantage of the availability of multiple computing resources.

Mechanistic understanding of Curium(III) sorption on natural K-feldspar surfaces

To assess a reliable safety case for future deep underground repositories for highly active nuclear waste the retention of radionuclides by the surrounding host rock must be understood comprehensively. Retention is influenced by several parameters such as mineral heterogeneity and surface roughness, as well as pore water chemistry (e.g., pH). However, the interplay between those parameters is not yet well understood. Therefore, we present a correlative spectromicroscopic approach to investigate sorption of the actinide Cm(III) on: 1) bulk K-feldspar crystals to determine the effect of surface roughness and pH (5.5 and 6.9) and 2) a large feldspar grain as part of a complex crystalline rock system to observe how sorption is influenced by the surrounding heterogeneous mineralogy. Our findings show that rougher K-feldspar surfaces exhibit increased Cm(III) uptake and stronger complexation. Similarly, increasing pH leads to higher surface loading and stronger Cm(III) binding to the surface. Within a heterogeneous mineralogical system sorption is further affected by neighboring mineral dissolution and competitive sorption between mineral phases such as mica and feldspar. The obtained results express a need for investigating relevant processes on multiple scales of dimension and complexity to better understand trivalent radionuclide retention by a potential repository host rock.

The Relationship Between Self-Esteem and Approval Dependence in University Students: The Serial Mediation of Interaction Anxiety and Insight

This research examined the serial mediating effect of interaction anxiety and insight into the relationship between self-esteem and approval dependence in university students. The research group comprised 511 volunteer university students, of whom 78,7% were females and 21,3% were males. Research data was collected via “The Two-Dimensional Self-Esteem Scale”, “The Scale of Interpersonal Relationship Dimensions”, “Interaction Anxiousness Scale”, and “Insight Scale”. In analysing the data, descriptive statistics were examined and the relationship between variables was calculated using the Pearson correlation coefficient. The bootstrap method was used to test the mediation model.The mediation analysis results revealed that interaction anxiety and insight functioned as mediation variables in the relationship between self-esteem and approval dependence. According to the findings, an increase in self-esteem causes a decline in interaction anxiousness, which causes an increase in insight, which in turn leads to a decline in approval dependence. Findings related to the model that was tested were discussed following the literature. Suggestions for researchers and field practitioners were listed.

The Role of Workplace Spirituality in Reducing Organizational Hypocrisy in Schools

In this research, the serial mediating effect of interaction anxiety and insight in the relationship between self-esteem and approval dependence in university students was examined. The study group of the research consists of 511 university students. Research data was collected via “Two-Dimensional Self-Esteem Scale”, “the Scale of Interpersonal Relationship Dimensions”, “Interaction Anxiousness Scale” and “Insight Scale”. Descriptive statistics were used in the analysis of the data, while Pearson Correlation Coefficient was used in determining the relationship between the variables, and Bootstrap method was used to test the mediation model. According to the mediation analysis results, it was revealed that interaction anxiousness and insight functioned as mediation variables in the relationship between self-esteem and approval dependence. According to the findings, increase in self-esteem causes a decline in interaction anxiousness, which causes an increase in insight, which in turn leads to a decline in approval dependence. Findings related to the model that was tested were discussed in accordance with the literature. Suggestions for researchers and field practitioners were listed. here to enter text.

Discovering the relevance of the personality of the destination brand - a literature review

Brand personality is highly significant for creating brand loyalty to withstand pressure in the highly competitive environment. Due to the cosmopolitanism and affordable traveling, people have become jaded and hard to surprise, thus, cities’ authorities must create smart destination brand personalities to attract more visitors. The aim of this paper is to gather the most popular city branding tools, trends and similarities through bibliometric study and present a broad view of the researches that have been conducted regarding destination brand personality. As a methodology, it uses a qualitative analysis which was made by exploring a scientific database. A common ground for all previous research on the topic tends to be the 5 Aaker’s Brand Personality Scale dimensions (1997) or extended to the 6 dimensions scale used in the most recent studies. The limitations of the research can indicate that there are still gaps in the literature connected to this topic, and the paper includes suggestions to fill them in. Most of the studies had focused on tourists’ perspective, and do not take residents’ views into consideration. As main results, we found that, research shows that young residents should be more involved into the destination’s branding process. Also, social media platforms as a marketing tool for promoting cities and gathering feedback from locals and tourists are understudied.

Scaling of voltage controlled magnetic anisotropy based skyrmion memory and its neuromorphic application

Voltage controlled skyrmion memory requires less energy compared to current controlled method where voltage changes magnetic anisotropy (VCMA) and Dzyaloshinskii-Moriya interaction (DMI). Ferromagnetic (FM) and synthetic antiferromagnetic (SAFM) memory devices are simulated using electric field control method where gate and gap width are chosen as smaller than skyrmion size so that skyrmion can feel the change in voltage polarity in the neighbouring gate and moves accordingly. Scaling of memory device is performed which shows SAFM memory can be made much narrower compared to FM memory as skyrmion diameter also depends on width of the structure. Effects of device structure and skyrmion-skyrmion repulsion force on skyrmion diameter variation are shown in cylindrical structure considering effect of demagnetizing field. Apart from these, neuromorphic application is considered where skyrmion moves from central square neuron region to surrounding synapse region or vice versa by the application of voltage. Switching time, voltage range, energy and scaling of device dimensions are shown for synapse-neuron having different number of skyrmions where multiple skyrmions represent different weight in the neuromorphic circuit.

PROBE2.0: A Systematic Framework for Routability Assessment From Technology to Design in Advanced Nodes

In advanced nodes, scaling of critical dimension and pitch has not progressed at historical Moore’s Law rates. Thus, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">scaling boosters</i> are explored to improve achievable power, performance, area, and cost (PPAC) in new technologies. However, scaling boosters increase complexity of standard-cell architectures, power delivery, design rules, and other aspects of the design enablement, and may not result in design-level benefits. Therefore, design-technology co-optimization (DTCO) methodologies are required to evaluate design-level benefits of scaling boosters. The key challenge for DTCO is that large engineering efforts and long timelines are needed to develop design enablements (e.g., cell libraries) and perform implementation studies in order to assess technology options. We describe a new framework that can systematically evaluate a measure of intrinsic routability, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K_{\mathrm{ th}}$ </tex-math></inline-formula> , across both technology and design choices. We focus on routability since it is a critical factor in the scaling of area and cost. Our framework includes realistic standard-cell libraries that are automatically generated using satisfiability modulo theory (SMT) methods, and a new pin shape selection method. Routability assessments are based on the PROBE approach and an improved construction of underlying netlist topologies. Our experimental studies demonstrate the assessment of routability impacts for advanced-node technology and design options. We demonstrate learning-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K_{\mathrm{ th}}$ </tex-math></inline-formula> prediction to reduce runtime, disk space and commercial tool licenses needed to implement our framework. Our work enables faster and more comprehensive evaluation of technology options early in the technology development process.