Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Efficient Process Monitoring Using Spatiotemporal PCA

Principal component analysis (PCA) has shown its high efficiency in process monitoring (PM). However, most of the existing PCA-based PM approaches only consider the spatial prior and ignore the temporal prior. Therefore, in this brief, we propose a novel PM framework using spatiotemporal PCA (STPCA), which incorporates both spatial and temporal priors. Technically, the spatial prior is integrated to preserve the cause-effect relationship of process variables, and the temporal prior is embedded to maintain the geometric structure of process samples. Moreover, an efficient optimization algorithm is developed using the alternating direction method of multipliers (ADMM) in a symmetric Gauss-Seidel (sGS) manner. Finally, the improved monitoring performance is verified on the benchmark Tennessee Eastman (TE) process. In particular, compared with PCA, the fault detection rate of fault IDV(20) is increased by 9.88%. This suggests that the proposed framework is promising for PM.
Hypocholesterolemic Effect of Analogue Rice with the Addition of Rice Bran

The objective of this study was to evaluate the hypocholesterolemic effect of analogue rice added with rice bran from three different rice varieties (white, red and black). The Sprague Dawley rats were fed ad libitum with six different chow formulas, i.e. standard diet equal to AIN-93G (C-), high-cholesterol diet (C+), high cholesterol diet plus analogue rice containing 15% coconut dregs flour (AR1), high cholesterol diet plus 10% rice bran from Ciherang white rice (AR2), Cere red rice (AR3), and Campoireng black rice (AR4). The diet intervention was conducted for 28 days. The total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C) and triglyceride (TG) of rat plasma as well as total fat of rat liver were analyzed. The results showed that rats fed with AR1, AR2, AR3 and AR4 exhibited significant decreases of TC, LDL-C, AI and liver fat, but increased of HDL-C in comparison to those of a high-cholesterol group (C+). This hypocholesterolemic effect is associated with the significant role of dietary fiber and/or -oryzanol. Among groups with diet containing rice bran, AR2 demonstrated the highest hypocholesterolemic effect followed by AR4 and AR3. The AR1 group also gave a significant hypochlolesterolemic effect (p<0.05) due to the role of the dietary fiber. As a conclusion, this study indicates that analogue rice added with rice bran and/or coconut dregs flour is a potential functional diet that is beneficial to lower the CHD risk.
Intersections between rural women’s resilience and quality of life: a mixed-methods study

Abstract Objective: to analyze the intersections between rural women’s quality of life and resilience. Method: convergent mixed methods design in which a cross-sectional quantitative study is triangulated with a qualitative study guided by Oral History. Data were collected concomitantly, using a socio-demographic form, Resilience Scale, Medical Outcomes Study 36-Item Short-Form Health Survey, and open-ended interviews. The analysis was based on descriptive and inferential statistics and inductive thematic analysis, which was integrated later. Results: an association was found between the social aspects domain of quality of life and a moderate level of resilience related to the characteristics of life in rural areas. The integration of results enabled verifying that these two constructs (which mutually influence each other) are mediated by protective factors, resilience developed by the rural women, such as spirituality and the formation of social support, enchantment, and a feeling of belonging to their context. Conclusion: by developing protective factors, rural women develop a resilient behavior that favors their quality of life. Identifying these factors enables the development of psychosocial interventions to promote rural women’s health.
PENGARUH AKUN INSTAGRAM JAVAFOODIE TERHADAP MINAT BELIKONSUMEN(ANALISIS REGRESI SEDERHANA PADA PENGUNJUNG STUDIO KOPI DI YOGYAKARTA)

The purpose of this research is to know the effect of social media for consumptive achievement at Studio Kopi. The method used in this research is description qualitative method. This research use interview and observation as the technique of gathering data. Researcher is interview on Studio Kopi in gathering data and use observation technique on java foodie instagram account Java foodie is one of social media that intense to visit by culinary, especially on instagram. The main theme java foodie is always on air or update about the menu food in jogja. The table on instagram showed that there are more than 45 K followers in Java foodie instagram account. For many things that share by Java foodie, there is a special place in jogja which serve unique menu, it is Studio Kopi. Main menu from Studio Kopi are cappuccino, Americano, and famous red velvet cake. The result show that social media especially instagram has effect to increase the human consumptive achievement, there are fulfilled the effective message and emotional message method. There is more efficient in time, place and money. Human will be fast to get information about menu on Studio kopi, so people feel exited. And it will make increasing the consumptive achievement at studio kopi
Research on Bi-LSTM machine reading comprehension algorithm based on attention mechanism

Machine reading comprehension is a very important research field in Natural Language Processing (NLP), but it is not sufficient for military research, and traditional machine reading comprehension algorithms do not fully explore every word in different contexts. In response to the above problems, this paper proposes a machine reading comprehension model that incorporates a multi-attention mechanism. It is brave to solve machine reading comprehension tasks in the military field. The model in this paper performs word embedding, part-of-speech embedding, and knowledge base embedding for each word in the article. Among them, knowledge embedding uses military knowledge bases to make up for the lack of information on military entities and relationships in military articles, and independently carries out part-of-speech embedding to solve the problem of part of speech judgment of polysemous words in specific contexts. The experimental results show that the machine reading comprehension model with multi-attention mechanism proposed in this paper can achieve better results on machine reading comprehension tasks, and the accuracy rate is improved by 1.6% compared with ROUGE-L.
Spatiotemporal variation in costs of managing protected areas

Funding for protected areas is limited and recurrent costs associated with managing these sites must be considered in planning their acquisition. However, most conservation planning studies either ignore management costs or use snapshot estimates, even though they vary through time. We surveyed expenditures on management made over 15 years for 37 protected areas in the Appalachians that were established by a large land trust (TNC). These management costs varied greatly through both time and space. We explored what ecological and socioeconomic characteristics explain this variation. Management costs increased with site area but exhibited economies of scale. They were also greater for sites presenting a more rugged terrain and surrounded by a denser combination of roads and urban areas. Prescribed burns were strong drivers of expenditures in the years they occur, while acquisition costs were negatively correlated to subsequent expenditures on management. Land managers felt that protected areas that received less management effort were in worse condition and tended to spend more on areas with greater estimated species richness. Better accounting of how management costs vary in space and time can help conservation organizations allocate their limited resources effectively and to evaluate the likely long‐term cost implications of expanding protected area networks.
A Practical Assessment of Using sUASs (Drones) to Detect and Quantify Wright Fishhook Cactus (Sclerocactus wrightiae L.D. Benson) Populations in Desert Grazinglands

Obtaining accurate plant population estimates has been integral in listing, recovery, and delisting species under the U.S. Endangered Species Act of 1973 and for monitoring vegetation in response to livestock grazing. Obtaining accurate population estimates remains a daunting and labor-intensive task. Small unmanned aircraft systems (sUASs or drones) may provide an effective alternative to ground surveys for rare and endangered plants. The objective of our study was to evaluate the efficacy of sUASs (DJI Phantom 4 Pro) for surveying the Wright fishhook cactus (Sclerocactus wrightiae), a small (1–8 cm diameter) endangered species endemic to grazinglands in the southwest desert of Utah, USA. We assessed sUAS-based remotely sensed imagery to detect and count individual cacti compared to ground surveys and estimated optimal altitudes (10 m, 15 m, or 20 m) for collecting imagery. Our results demonstrated that low altitude flights provided the best detection rates (p < 0.001) and counts (p < 0.001) compared to 15 m and 20 m. We suggest that sUASs can effectively locate cactus within grazingland areas, but should be coupled with ground surveys for higher accuracy and reliability. We also acknowledge that these technologies may have limitations in effectively detecting small, low-growing individual plants such as the small and obscure fishhook cactus species.
Design of Mono Stage Luo Converter for Electric Vehicles Charging System

The electric vehicle charger with modified LUO converter is proposed in this paper that has High Frequency Transformer (HFT) to isolate the input and load side. The primary of the HFT contains two switches and two diodes that reduces the voltage stress in switches. The proposed topology operates in Discontinuous Conduction Mode (DCM), which reduces the components and control complexities of the converter. The charger is operated in Constant Voltage (CV) - Constant Current (CC) modes, which increases the battery life at long term. The proposed topology delivers better performance that is evaluated by performing the simulation in MATLAB/Simulink. The resultant output voltage from modified LUO converter charges the battery of 48V.
Watermarking-Based Protection Strategy Against Stealthy Integrity Attack on Distributed State Estimation

This article studies the security of distributed state estimation under data integrity attacks. Each sensor is equipped with a Kullback–Leibler (K–L) divergence detector to diagnose the authenticity of the received data. A necessary and sufficient condition for the insecurity of the distributed estimator is derived, in which the stealthy attack can evade the detector and degrade the estimation performance. Furthermore, an algorithm is proposed to generate stealthy attack sequences. To overcome the vulnerability, a data transmission strategy based on watermarking is proposed. The effect of the watermarking parameters on the attack in different scenarios is subsequently analyzed. It is proved that the K–L divergence detector can effectively distinguish the stealthy attack with the help of the proposed strategy, thereby ensuring the security of the distributed state estimator. Compared with traditional encryption mechanisms, the proposed strategy neither increases the computational complexity nor sacrifices the estimation performance in the absence of attacks. A simulation example is presented to demonstrate the effectiveness of the developed approach.
Gliotransmitter-based modulation of presynaptic efficacy provides a feedback between neuronal activity and astrocytic transients

Astrocytes not only provide for the transfer of nutrients between blood vessels and neurons, but also take part in signaling through nerve tissue and regulate formation, pruning, and plasticity of synapses. Analysis of the impact of the astrocytic domain organization on the local and collective dynamics of neurons is needed for both the fundamental understanding of the mechanisms underlying cognition and for the creation of new methods of neurodegenerative pathology treatment targeted at non-neuronal cells without direct effects on the neural network. Based on the available experimental data, we propose a model study of the role of astrocytic calcium signaling in the regulation of synaptic transmission between neurons in order to elucidate the role played by astrocyte calcium signaling in signaling pathways regulating neural activity. The proposed model is based on the following assumptions: (i) localized release of gliotransmitters depends on the spatiotemporal patterns of calcium activity and is determined by cell morphology and topology of the entire network; (ii) the release of gliotransmitters can lead to spatial segregation of the nervous tissue into regions in which different conditions are maintained, favoring for increased or decreased synaptic efficacy.
Commitment of employees: The case of dormitory service administration at higher education in Beijing, China

Employees’ commitment is pertinent for the effectiveness of any higher education administration. This study aimed to explore the commitment of employees working at the dormitory service administration at a national key university in Beijing. By adopting the quantitative methodology, a questionnaire of 10 statements with three- point Likert scale was designed and handed out to 25 employees through following the convenience sampling technique. Data was analyzed using frequency counts (i.e. number of responses) and percentages. The results showed high commitment among dormitory service administration employees.
Quantum chemistry study in metallophilic interactions on complexes based in Au(I)-Pb(II) and Au(I)-Bi(III)

ABSTRACT The present work consists of a study that describes the metallophilic interaction in dimers of hypothetical complexes of Au(I), Pb(II), and Bi(III). Quantum chemistry methods based on MP2, SCS-MP2, CCSD(T), and DFT have been applied, verifying an attraction only when the electronic correlation is included. The attraction is attributed to dispersion effects. It is obtained equilibrium distances and interaction energies gold-metal for the different models. The influence of the attraction among metals in processes such as absorption energy is evaluated, finding that there is the participation of orbitals of the metallic atoms in the electronic transitions involved.
Wide Range Applications of Spirulina: From Earth to Space Missions

Spirulina is the most studied cyanobacterium species for both pharmacological applications and the food industry. The aim of the present review is to summarize the potential benefits of the use of Spirulina for improving healthcare both in space and on Earth. Regarding the first field of application, Spirulina could represent a new technology for the sustainment of long-duration manned missions to planets beyond the Lower Earth Orbit (e.g., Mars); furthermore, it could help astronauts stay healthy while exposed to a variety of stress factors that can have negative consequences even after years. As far as the second field of application, Spirulina could have an active role in various aspects of medicine, such as metabolism, oncology, ophthalmology, central and peripheral nervous systems, and nephrology. The recent findings of the capacity of Spirulina to improve stem cells mobility and to increase immune response have opened new intriguing scenarios in oncological and infectious diseases, respectively.
Design of Variation-Tolerant Circuits for Nanometer CMOS Technology: Circuits and Architecture Co-Design

Aggressive scaling of CMOS technology in sub-90nm nodes has created huge challenges. Variations due to fundamental physical limits, such as random dopants fluctuation (RDF) and line edge roughness (LER) are increasing significantly with technology scaling. In addition, manufacturing tolerances in process technology are not scaling at the same pace as transistor’s channel length due to process control limitations (e.g., sub-wavelength lithography). Therefore, within-die process variations worsen with successive technology generations. These variations have a strong impact on the maximum clock frequency and leakage power for any digital circuit, and can also result in functional yield losses in variation-sensitive digital circuits (such as SRAM). Moreover, in nanometer technologies, digital circuits show an increased sensitivity to process variations due to low-voltage operation requirements, which are aggravated by the strong demand for lower power consumption and cost while achieving higher performance and density. It is therefore not surprising that the International Technology Roadmap for Semiconductors (ITRS) lists variability as one of the most challenging obstacles for IC design in nanometer regime. To facilitate variation-tolerant design, we study the impact of random variations on the delay variability of a logic gate and derive simple and scalable statistical models to evaluate delay variations in the presence of within-die variations. This work provides new design insight and highlights the importance of accounting for the effect of input slew on delay variations, especially at lower supply voltages. The derived models are simple, scalable, bias dependent and only require the knowledge of easily measurable parameters. This makes them useful in early design exploration, circuit/architecture optimization as well as technology prediction (especially in low-power and low-voltage operation). The derived models are verified using Monte Carlo SPICE simulations using industrial 90nm technology. Random variations in nanometer technologies are considered one of the largest design considerations. This is especially true for SRAM, due to the large variations in bitcell characteristics. Typically, SRAM bitcells have the smallest device sizes on a chip. Therefore, they show the largest sensitivity to different sources of variations. With the drastic increase in memory densities, lower supply voltages and higher variations, statistical simulation methodologies become imperative to estimate memory yield and optimize performance and power. In this research, we present a methodology for statistical simulation of SRAM read access yield, which is tightly related to SRAM performance and power consumption. The proposed flow accounts for the impact of bitcell read current variation, sense amplifier offset dis-
Assessment of Thermal Aging of Aluminum Alloy by Acoustic Nonlinearity Measurement of Surface Acoustic Waves

ABSTRACT Acoustic nonlinearity measurements via contact and noncontact generations of surface acoustic waves (SAWs) were performed in order to characterize the thermal aging of aluminum alloy. The experiments were conducted on aluminum alloy samples (Al6061-T6) that were heat-treated at 220°C for different times (0 min, 20 min, 40 min, 1 h, 2 h, 10 h, 100 h, 1,000 h) and thus had the different levels of thermal aging. The acoustic nonlinearity of the specimens in two types of SAWs was observed according to the thermal aging. The fractional changes in the acoustic nonlinearity exhibited similar trends in both contact and noncontact SAWs, showing that the acoustic nonlinearity measurement via SAWs is independent of the SAW-excitation method. Furthermore, the fractional changes agreed well with the variation in the yield strength, which was a minimum when the acoustic nonlinearity reached its first peak. Then, the acoustic nonlinearity drastically dropped while the yield strength increased to its highest value. Thus, the variation in the acoustic nonlinearity can be perceived as an indicator of the aging level. These results demonstrate the potential feasibility of acoustic nonlinearity measurements via SAWs for the nondestructive evaluation of material degradations.
Fashion E-Tail and the Impact of Returns: Mapping Processes and the Consumer Journey towards More Sustainable Practices

The purpose of this study is to trace the processes behind the elaboration of the product page and map the shopping journey to identify ways to reduce returns. This is a qualitative study conducted in three stages: exploratory interviews with users, semi-structured interviews with e-commerce and logistics specialists, and directed storytelling sessions with users. Our findings indicate that the e-commerce specialists are not fully aware of the impacts caused by the high return rates, and product presentation pages are therefore not elaborated to provide users with all the information necessary to make accurate purchases. Sellers should improve product presentation pages to increase product knowledge by providing tools to enhance quality mental imagery. Additionally, sellers should inform consumers of the impact of their shipping options and returning habits. There are ways to optimize logistics processes to reduce the environmental impact. Prior research has addressed these issues separately. Besides, have addressed mental imagery to increase sales. This study brings a holistic approach and brings mental imagery as a tool to provide users with more information about a product.
Research on Coverage Optimization in a WSN Based on an Improved COOT Bird Algorithm

To address the problems of uneven distribution and low coverage of wireless sensor network (WSN) nodes in random deployment, a node coverage optimization strategy with an improved COOT bird algorithm (COOTCLCO) is proposed. Firstly, the chaotic tent map is used to initialize the population, increase the diversity of the population, and lay the foundation for the global search for the optimal solutions. Secondly, the Lévy flight strategy is used to perturb the individual positions to improve the search range of the population. Thirdly, Cauchy mutation and an opposition-based learning strategy are fused to perturb the optimal solutions to generate new solutions and enhance the ability of the algorithm to jump out of the local optimum. Finally, the COOTCLCO algorithm is applied to WSN coverage optimization problems. Simulation results show that COOTCLCO has a faster convergence speed and better search accuracy than several other typical algorithms on 23 benchmark test functions; meanwhile, the coverage rate of the COOTCLCO algorithm is increased by 9.654%, 13.888%, 6.188%, 5.39%, 1.31%, and 2.012% compared to particle swarm optimization (PSO), butterfly optimization algorithm (BOA), seagull optimization algorithm (SOA), whale optimization algorithm (WOA), Harris hawks optimization (HHO), and bald eagle search (BES), respectively. This means that in terms of coverage optimization effect, COOTCLCO can obtain a higher coverage rate compared to these algorithms. The experimental results demonstrate that COOTCLCO can effectively improve the coverage rate of sensor nodes and improve the distribution of nodes in WSN coverage optimization problems.