Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrospray Printing of Polyimide Films for Electronics Packaging Applications

Electrospray printing utilizes a strong electric potential to atomize a precursor ink solution into a spray of electrically- charged microdroplets containing the print material. The carrier solvent rapidly evaporates while the droplets are in-flight, leaving behind dry material which can be delivered to a substrate to create a film. Here we report on electrospray printing of polyimide, a critical material in electronics packaging. Polyimide films were printed onto flat silicon substrates, as well as industry-standard 20-μm diameter bond wires and pads. The films printed onto silicon were analyzed for their dielectric breakdown strength and surface wettability. Thicker films were able to achieve breakdown potentials exceeding 1kV, however breakdown field strength was greater for thinner films resulting in a maximum sustained field strength of 127 V/μm. The printed films were also moderately hydrophobic, with an average contact angle of 110°. Polyimide films printed onto the bond wire and bond pads displayed a high degree of conformality. Printing times as low as 5 minutes produced conformal coatings around the 20-μm bond wires. Salt- water immersion and salt-spray testing were conducted to evaluate corrosion protection of the printed polyimide films. Wire bonds with a printed polyimide coating survived up to 10 times longer in a corrosive environment than those without a coating.
A Intrusion Detection Model Based on Convolutional Neural Network and Feature Selection

With the rapid development of the Internet, the network security situation has become increasingly severe. Attackers around the world have caused thousands of economic losses to government and enterprises. Novel attack methods have brought huge challenges to traditional intrusion detection systems. This paper proposes an intrusion detection model based on deep learning. First it uses the Sigmoid pigeon optimization algorithm(SPIO) to select the features of the data samples, then uses a Three-layer convolutional neural network trains and validates the dataset. The model is tested on NSL-KDD dataset. Experimental results show that this model has a higher accuracy rate than the existing traditional detection models.
Forecasting of WTI crude oil using combined ANN-Whale optimization algorithm

ABSTRACT The current study predicts West Texas Intermediate (WTI) petroleum prices using an artificial neural network (ANN) with a whale optimization algorithm (WOA). In implementing the model, five parameters, including gold price, coal price, natural gas price, Dollar-Euro exchange rate, and Dollar-Yuan exchange rate, have been used as input to the combined model. The intelligent and basic ANN algorithm results compared to finding the ANN-WOA algorithm capacity in predicting the future price of WTI oil. ANN-WOA model improved the WTI price predicting accuracy up to 22% compared to the ANN. The ANN-WOA method with a value of R2 = 0.93 compared to the ANN method with a value of R2 = 0.75 was able to reduce the model error well. According to the significant impact that the input parameters of the combination model had on the WTI oil price prediction, therefore, in studies that predict price or other variables, highly correlated variables can significantly increase the accuracy of the forecast.
Does firm diversity-enhancement program bundle matter? Firm performance dimensions, employee ownership program, and environmental technological opportunity

Abstract Research on diversity programs provides inconclusive knowledge regarding their effect on firm performance. In this study, we build on the Ability-Motivation-Opportunity framework to examine the relationship between firm diversity-enhancement program bundle and firm performance. Based on a dataset covering 2,794 U.S. publicly listed firms over 15 years, we find support for our hypothesis that firm diversity-enhancement program bundle results in a greater pay-off when it is coupled with a stronger employee ownership program at the firm level or a greater technological opportunity at the industry level. Furthermore, the pay-off is greatest when a firm’s diversity-enhancement program bundle, its employee ownership program, and its environmental technological opportunity are all high. Overall, our study provides nuanced theoretical and empirical accounts regarding a firm’s integrated diversity-enhancement efforts. It also provides novel managerial implications regarding when firms can reap the most benefit from their integrated diversity-enhancement efforts.
Creative delinquency or destructive selfishness?

We study two competing firms with different production costs and moral standards making decisions to sell their products in the market by choosing their optimal production quantities and degrees of disobedience of a guiding rule imposed by a regulatory authority such as the government. We model this problem as a Cournot–Nash game in which. We introduce rules unfairness as a behavioural factor at work. We answer the questions of why firms disobey rules and to what degree and what are the effects of such actions. Our results show that firms disobey the rules for self-interest and harm other incentives. The case when the firms’ disobediences can improve the total surplus (sum of their profits) is referred to as creative delinquency, whereas destructive selfishness refers to situation in which one’s behaviour only benefits self and leads to a decreased total surplus. Our results indicate that rules unfairness could be beneficial in some cases. Finally, our derivation of the optimal decision rules allows a regulatory authority to put into effect a coordinated punishment strategies that can benefit one firm or both firms.
Do the Firms Utilize Market Timing? Capital Structure of Restaurant Firms by Pecking Order and Market Timing Theories

ABSTRACT The purpose of this study is to examine whether restaurant firms prefer debt to equity financing and utilize market timing well in equity financing during firm value maximization. For this purpose, two theories were applied – pecking order and market timing. Secondary financial data was collected from restaurant firms based in the United States. Subsequently, bivariate correlation, fixed and random effects, and pooled Ordinary Least Square (OLS) analyses were performed on the statistical data. The analysis outcomes support the pecking order theory, meaning that restaurant firms rely significantly on debt over equity in financing decisions. The analysis outcomes of the market timing proxy indicate that restaurant firms either do not use market timing enough or do not have a sufficient window of opportunity (firm value maximization) for equity financing. Although the restaurant industry has a relatively higher liability ratio than other industries, its financing decisions combining debt and equity have never been examined. The theoretical and managerial implications have been suggested in terms of balancing debt and equity financing decisions and the influence of corporate governance structure on financing decisions.
Analyzing the Interactions of Monetary and Fiscal Policy in a Small Open Economy Using a DSGE Model

The principal aim of this paper is to estimate a small open economy dynamic stochastic general equilibrium (DSGE) model with monetary and fiscal policy and analyze the interaction of these policies in Hungary. In the paper we present the model in a log-linearized form. We combine both calibration and Bayesian estimation to obtain parameter values of the model. We find that the model is suitable for impulse response analysis, so we estimate the impulse response functions of the model. We examine how five endogenous variables – namely output, inflation, the nominal interest rate, government spending and government revenue – react to non-systematic shocks to the nominal interest rate, government spending and government revenue. The plotted impulse response functions allow us to study how monetary and fiscal policy interacts in a small open economy. In some cases we find that restrictive fiscal policy is accompanied by expansive monetary policy, while in other cases the policy responses to shocks are coordinated. We conclude that our results are in accordance with economic theory.
Fatigue Pictogram: an option for assessing fatigue severity and impact

The purpose of this paper was to validate the Fatigue Pictogram for use in Brazil. Data was collected at four oncology ambulatory clinics in Sao Paulo (Brazil) and at the Nursing School of Sao Paulo University. A convenience sample of 584 cancer patients, 184 caregivers and 189 undergraduate nursing students completed the Karnofsky Scale, Fatigue Pictogram-Brazilian Version, and the Beck Depression Inventory (BDI). Validity and reliability tests were performed. Test-retest showed that the instrument has good stability. The first item of the Fatigue Pictogram discriminated students from caregivers and patients but not patients from caregivers. The second item discriminated among all groups. Adequate convergent (fatigue and depression) and divergent (fatigue and Karnofsky Scale) validity was observed. The Fatigue Pictogram is a valid, reliable, and easy-to-use tool for assessment of cancer-related fatigue but needs adjustments for use among healthy individuals.
Xiao-Chai-Hu Decoction Ameliorates Poly (I:C)-Induced Viral Pneumonia through Inhibiting Inflammatory Response and Modulating Serum Metabolism

Viral pneumonia is widespread, progresses rapidly, and has a high mortality rate. Developing safe and effective therapies to treat viral pneumonia can minimize risks to public health and alleviate pressures on the associated health systems. Xiao-Chai-Hu (XCH) decoction can be used in the treatment of viral pneumonia. However, the mechanisms of XCH on viral pneumonia remain unclear. In this study, poly (I:C) was used to establish a mouse model of viral pneumonia, and the therapeutic effects of XCH on viral pneumonia were assessed. Furthermore, we evaluated the effects of XCH on inflammatory response. Lastly, untargeted metabolomics were used to study the metabolic regulatory mechanisms of XCH on viral pneumonia model mice. Our results showed that XCH treatment decreased the wet/dry ratio in lung tissue, total protein concentration, and total cell count in bronchoalveolar lavage fluid (BALF). H&E staining indicated that XCH treatment alleviated the pathological changes in lung. Moreover, XCH treatment decreased the levels of proinflammatory cytokines (IL-1β, IL-6, and TNF-α) and lowered the ratio of CD86+/CD206+ macrophages and CD11b+LY6G+ neutrophils in BALF. XCH treatment also decreased the myeloperoxidase (MPO) and reduced the phosphorylations of PI3K, AKT, and NF-κB p65 in lung. Serum untargeted metabolomics analysis showed that XCH treatment could affect 18 metabolites in serum such as creatine, hydroxyproline, cortisone, hydrocortisone, corticosterone, hypotaurine, and taurine. These metabolites were associated with arginine and proline metabolism, steroid hormone biosynthesis, and taurine and hypotaurine metabolism processes. In conclusion, our study demonstrated that treatment with XCH can ameliorate viral pneumonia and reduce inflammatory response in viral pneumonia. The mechanism of action of XCH in the treatment of viral pneumonia may be associated with inhibiting the activation of PI3K/AKT/NF-κB signaling pathway in lung and regulating arginine and proline metabolism, steroid hormone biosynthesis, and taurine and hypotaurine metabolism in serum.
Effect of artificial food on the survival and growth tadpoles of Hoplobatrachus occipitalis (Günther 1858) in pond-raised

The current study aimed at evaluating the effect of artificial food on the survival and growth tadpoles of Hoplobatrachus occipitalis in rectangular enclosures (2 m x 1 m x 0.5 m) placed in a pond until the onset of metamorphosis. Three different mediums: medium 1 (E1) = tadpoles fed with artificial food containing 27% protein, medium 2 (E2) = tadpoles fed with spirulina and medium 3 (E3) = no-fed tadpoles were tested in triplicate on tadpoles of initial weight 0.04 g. The tadpoles were fed daily at 10% of their biomass at a frequency of 3 times/day. After 28 days of rearing, the highest final weight, final length, specific growth rate and survival rate, respectively 2.16 ± 0.21 g, 62.59 ± 1.81 mm, 1328 ± 0.32% and 80.33% were recorded with tadpoles of medium 1 fed with the artificial food containing 27% protein. Growth and feed utilization parameters recorded in medium E1 tadpoles were significantly higher (p˂0.05) compared to other culture mediums. The results obtained show the possibility of rearing the tadpoles of Hoplobatrachus occipitalis with an artificial feed in a pond.
AMPK and Diseases: State of the Art Regulation by AMPK-Targeting Molecules

Simple Summary AMPK is an enzyme that plays a role in cellular energy mechanisms and controls many metabolic and physiological processes. AMPK is dysregulated in different diseases, making it a potential therapeutic target. AMPK can be activated in a direct or indirect way. In this review, we discuss different AMPK activating compounds and especially focus our attention on those compounds that imitate physiological mechanisms of AMPK activation. Abstract 5′-adenosine monophosphate (AMP)-activated protein kinase (AMPK) is an enzyme that regulates cellular energy homeostasis, glucose, fatty acid uptake, and oxidation at low cellular ATP levels. AMPK plays an important role in several molecular mechanisms and physiological conditions. It has been shown that AMPK can be dysregulated in different chronic diseases, such as inflammation, diabetes, obesity, and cancer. Due to its fundamental role in physiological and pathological cellular processes, AMPK is considered one of the most important targets for treating different diseases. Over decades, different AMPK targeting compounds have been discovered, starting from those that activate AMPK indirectly by altering intracellular AMP:ATP ratio to compounds that activate AMPK directly by binding to its activation sites. However, indirect altering of intracellular AMP:ATP ratio influences different cellular processes and induces side effects. Direct AMPK activators showed more promising results in eliminating side effects as well as the possibility to engineer drugs for specific AMPK isoforms activation. In this review, we discuss AMPK targeting drugs, especially concentrating on those compounds that activate AMPK by mimicking AMP. These compounds are poorly described in the literature and still, a lot of questions remain unanswered about the exact mechanism of AMP regulation. Future investigation of the mechanism of AMP binding will make it possible to develop new compounds that, in combination with others, can activate AMPK in a synergistic manner.
Phonemes in language development in elementary school students

In alphabetic languages like ours, learning to write requires awareness of the phonological structure of speech. Phonological awareness is the ability to access the structure of the oral language and be aware of the phonological segments of words. The purpose of the work is to carry out an analysis on the importance of the teaching of phonemes, as a key element for the development of the subject of language in the students at elementary school of the Educational Unit Fisco Misional Cinco de Mayo of the Chone Canton in the period 2021-2022, as well as the strong relationship that exists between the development of oral language and the skills that favor phonological knowledge in elementary school students. The research is based on a bibliographic review and descriptive work, which made it possible to characterize the impact of phonemes on the development of language in elementary school students and it was possible to verify the strong relationship that exists between the development of oral language and the skills that favor phonological knowledge in students.
Guest Speakers and Sexuality Education: An Ethnographic Look inside One California High School

Abstract Adopting an ethnographic lens, readers are provided a look inside a California high school sexuality education classroom. On this chosen day, two invited guest speakers from an outside company are teaching students about pregnancy prevention, healthy relationships, and risks associated with having sex. Analysis of the guest speakers’ pedagogical strategies and accompanying curricula reveal exclusionary abstinence-only ideologies that provide students with limited and narrow constructions of commitment, romance, love, and sexuality. Although considered to be a comprehensive and inclusive sexuality education classroom space, content delivery strategically instills fear and disseminates misinformation. Through classroom observations and student interviews, findings highlight the need for increased attention to guest speakers’ involvement in sexuality education classrooms.
VR What We Eat: Guidelines for Designing and Assessing Virtual Environments as a Persuasive Technology to Promote Sustainability and Health

Environmental sustainability has grown as a topic of interest in the scientific community and has gained mainstream attention. This paper focuses on issues to consider when designing and assessing the effectiveness of virtual reality (VR) as persuasive technology. We propose a set of research guidelines to inform future work on how to enhance VR’s effectiveness as a persuasive tool. We present animal product consumption as an example to demonstrate how these guidelines can be applied to a real-world problem that relates to sustainability and health. We describe a set of guidelines for advancing research on VR as a persuasive tool and provide examples of how they can be applied in future research.
Iterative Mesh Modification Planning: A new Method for Automatic Disassembly Planning of Complex Industrial Components

Automatic disassembly planning for complex industrial products like vehicles checks the expandability of components already at early stages of design. For a fast computation of collision-free disassembly paths, sampling-based rigid body motion planning is used in the literature. However, in real-world scenarios there are circumstances that prevent the finding of plausible collision-free disassembly paths with these conventional motion planners. The most difficult problem is that many components have deformable fastening elements that are modeled in a relaxed state and often as a part of the rigid object. The fastening elements cause unavoidable collisions of the component with its environment along the actual disassembly path. In this paper, we present Iterative Mesh Modification Planning (IMMP). Given the information about fastening elements in advance, our method applies a controlled iterative process of geometric deformations and planning attempts to the component to be disassembled. With this process, we are able to disassemble the component from its installed position with a conventional rigid body motion planner taking fastening elements and also overpressure into account. We demonstrate the effectiveness of our method on real-world planning scenarios from the automotive industry.
Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation

The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of technology and the widespread use of the internet. Disambiguation is the best tool for avoiding the problem of misperception. The most important feature of this approach is that words with multiple meanings of nouns can be easily disambiguated according to the sense of the sentences. As a result of incorporating all of these factors, This Work will concentrate on the Accuracy of adjectives and verbs. Many natural languages, including English, German, Arabic, Assamese, and others, propose different methodologies; however, work on Word Sense Disambiguation in Hindi is limited. For Hindi Word Sense Disambiguation, the proposed algorithm employs a genetic algorithm. The dynamic configuration window function is used, including the ambiguous terms left and right. The central tenet of this method is that the target term and its surroundings share a common topic. With approximately 65.17%, 72%, and 74.1 %, respectively, the proposed work has compared to existing approaches such as graph-based approaches, association rules approaches, and probabilistic latent semantic analysis approaches. The proposed method has an accuracy of 80%, which indicates that it improves the existing work by 8% in terms of Accuracy and other parameters. Results show that the proposed work generates more accurate results for Hindi word sense disambiguation.
A Comparative Analysis of SRAM Sense Amplifiers

Author(s): Shi, Kejian | Advisor(s): Abidi, Asad A | Abstract: The operation of the voltage-mode and current-mode sense amplifiers (VSA and CSA) is explained in detail. Analytical expressions for offset arising from random FET mismatch are derived. The mechanism of two offset reduction method for VSA is explained. The supply-dependent offset for CSA is shown. The offset combined with signal attenuation define a figure-of-merit. The current-mode sense amplifier is shown to be superior at VDD l 0.6 ~ 0.7V.
Network Modeling of Complex Time-Dependent Changes in Patient Adherence to Adjuvant Endocrine Treatment in ER+ Breast Cancer

Early patient discontinuation from adjuvant endocrine treatment (ET) is multifactorial and complex: Patients must adapt to various challenges and make the best decisions they can within changing contexts over time. Predictive models are needed that can account for the changing influence of multiple factors over time as well as decisional uncertainty due to incomplete data. AtlasTi8 analyses of longitudinal interview data from 82 estrogen receptor-positive (ER+) breast cancer patients generated a model conceptualizing patient-, patient-provider relationship, and treatment-related influences on early discontinuation. Prospective self-report data from validated psychometric measures were discretized and constrained into a decisional logic network to refine and validate the conceptual model. Minimal intervention set (MIS) optimization identified parsimonious intervention strategies that reversed discontinuation paths back to adherence. Logic network simulation produced 96 candidate decisional models which accounted for 75% of the coordinated changes in the 16 network nodes over time. Collectively the models supported 15 persistent end-states, all discontinued. The 15 end-states were characterized by median levels of general anxiety and low levels of perceived recurrence risk, quality of life (QoL) and ET side effects. MIS optimization identified 3 effective interventions: reducing general anxiety, reinforcing pill-taking routines, and increasing trust in healthcare providers. Increasing health literacy also improved adherence for patients without a college degree. Given complex regulatory networks’ intractability to end-state identification, the predictive models performed reasonably well in identifying specific discontinuation profiles and potentially effective interventions.