Miracle-dz/UniFAR-FTUs huggingface dataset:
Design Equations for Spiral and Scalable Cross Inductors on 0.35 μm CMOS Technology

This paper presents a set of design equations for spiral and new scalable cross inductors in CMOS 0.35 μm technology, relating electrical parameters of the inductor’s equivalent circuit as functions of its geometric dimensions. The procedure used to derive the design equations is described and involves electromagnetic simulation of inductors with different geometric dimensions, extraction of values for equivalent circuit model elements for each inductor and the use of multivariate regression analysis applied to generalized linear models (GLM) based on design of experiments (DoE). A p-type nine elements equivalent electrical circuit was used for the inductors, where all elements values are constants, allowing simulation on SPICE-like softwares. Results from the models obtained for both spiral and scalable cross inductors presented close match to the simulated results.
Methods for Multidimensional Event Classiﬁcation: A Case Study

: We present results from a case study comparing diﬀerent classiﬁcation methods, using as input a set of Monte Carlo data, generated and approximately triggered and preprocessed for an imaging gammaray Cherenkov telescope. Such data belong to two classes, originating either from incident gamma rays or caused by hadronic showers. There is a weak discrimination between signal (gamma) and background (hadrons), and thus the data provide an excellent proving ground for classiﬁcation techniques. The data are brieﬂy described, the methods are presented, and a comparison of the results is made. Several methods give results comparable within small ﬂuctuations, suggesting that they perform at or close to the Bayesian limit of achievable separation. Other methods give clearly inferior or inconclusive results. Some problems that this study can not address are also discussed. Abstract We present results from a case study comparing diﬁerent classiﬂcation methods, using as input a set of Monte Carlo data, generated and approximately triggered and pre-processed for an imaging gamma-ray Cherenkov telescope. Such data belong to two classes, originating either from incident gamma rays or caused by hadronic showers. There is a weak discrimination between signal (gamma) and background (hadrons), and thus the data provide an excellent proving ground for classiﬂcation techniques. The data are brie(cid:176)y described, the methods are presented, and a comparison of the results is made. Several methods give results comparable within small (cid:176)uctuations, suggesting that they perform at or close to the Bayesian limit of achievable separation. Other methods give clearly inferior or inconclusive results. Some problems that this study can not address are also discussed.
On the dynamics of the Kugo-Ojima function

In this talk, after reviewing the dynamical gluon mass generation mechanism within the pinch technique framework and its phenomenological predictions, we will introduce the modern formulation of the pinch technique which makes extensive use of the Batalin-Vilkovisky quantization formalism. In this framework a certain auxiliary function Λμν(q) ‐ and its associated form factors G(q 2 ) and L(q 2 ) ‐ play a prominent role. After showing that in the (background) Landau gauge Λμν(q) fully constrains the QCD ghost sector, we show that G(q 2 ) coincides with the KugoOjima function u(q 2 ), whose infrared behavior has traditionally served as the st andard criterion for the realization of the Kugo-Ojima confinement mechanism . The determination of the behavior of G(q 2 ) (and therefore of the Kugo-Ojima function) for all momenta through a combination of the available lattice data on the gluon and ghost propagator s as well as the dynamical equation G(q 2 ) satisfies, will be then discussed. In particular we will show that (i) in the deep infrared the function deviates considerably from the value associated with the realization of the Kugo-Ojima confinement scenario, and ( ii) establish the dependence on the renormalization point of u(q 2 ), and especially of its value at q 2 = 0.
Research , part of a Special Feature on Designing Transformative spaces for sustainability in social-ecological systems Stories in social-ecological knowledge cocreation

Transformations in social-ecological systems to overturn poverty and ecosystem degradation require approaches to knowledge synthesis that are inclusive and open to creative innovation. We draw on interviews with participants and in-depth process observation of an iterative knowledge cocreation process in Kenya and Mozambique that brought together scientists, community representatives, government representatives, and practitioners who had expertise or experience in poverty and/or coastal natural resource use and management. We analyze the communicative spaces opened by techniques of system diagrams and future scenarios, and provide a rich account of the emergent process of developing a “shared conceptual repertoire” as a basis for effective communication and knowledge synthesis. Our results highlight the difficulties of challenging dominant narratives and the creative potential that exists in reflecting on their underpinning assumptions. In our analysis, stories and lived experiences emerged as key means shaping the construction of shared concepts and ideas. We conclude by outlining the implications of designing knowledge cocreation processes that support the task of devising systemic interventions that are robust for a range of future scenarios. This includes embracing the role of stories in generating shared meanings and opening up spaces for exploration of knowledge assumptions that are embedded in intervention narratives.
PERSISTENCE AND TOXICITY OF TWO PLANT EXTRACTS TO SOME STORED PRODUCT INSECTS

This work aims at evaluation the efficiency of the acetone and petroleum ether extracts of Cubeb fruits Piper cubeba (L.) and Thyme flowering buds Thymus vulgaris (L.) against the adults of Sitophilus oryzae (L.), Rhizopertha dominica (F.) and Tribolium castaneum (Herbst). Also, persistence of the two plant extracts compared to malathion and pirimiphos- methyl (actellic) using the most sensitive insect species (S. oryzae), was investigated . Results showed that , the efficiency of the two plant extracts was concentration and exposure period –dependent. At the highest tested concentrations (2&1%w/w), the acetone extract of P. cubeba and petroleum ether extract of T. vulgaris were highly effective against S. oryzae and R.dominica adults, while, T. castaneum adults were the least sensitive . On the other hand, the petroleum ether extract of P.cubeba and the acetone extract of T.vulgaris indicated lower effectiveness against the three tested insects even after two weeks from treatment. The results also showed that, malathion and pirimihos methyl indicated clearly longer residual toxicity than the two plant extracts.
Institutional Knowledge at Singapore Management University Dynamic label propagation in social networks

Label propagation has been studied for many years, starting from a set of nodes with labels and then propagating to those without labels. In social networks, building complete user proﬁles like interests and aﬃliations contributes to the systems like link prediction, personal-ized feeding, etc. Since the labels for each user are mostly not ﬁlled, we often employ some people to label these users. And therefore, the cost of human labeling is high if the data set is large. To reduce the expense, we need to select the optimal data set for labeling, which produces the best propagation result. In this paper, we proposed two algorithms for the selection of the optimal data set for labeling, which is the greedy and greedyMax algorithms according to diﬀerent user input. We select the data set according to two scenarios, which are 1) ﬁnding top-K nodes for labeling and then propagating as much nodes as possible, and 2) ﬁnding a minimal set of nodes for labeling and then propagating the whole network with at least one label. Furthermore, we analyze the network structure that aﬀects the selection and propagation results. Our algorithms are suitable for most propagation algorithms. In the experiment part, we evaluate our algorithms based on 500 networks extracted from the ﬁlm-actor table in freebase according to the two diﬀerent scenarios. The performance including input percentage, time cost, precision and f1-score were present in the results. And from the results, the greedyMax could achieve higher performance with a balance of precision and time cost than the greedy algorithm. In addition, our algorithm could be adaptive to the user input in a quick response.
VALIDATION OF SOIL-SITE MODELS

Hundreds of soil-site models have been published without being validated; such models may have prediction bias. The potential for prediction bias is especially high when many candidate predictor variables from a small sample are tested for during model development. Because of po tential prediction bias, all soil-site models must be vali dated before being accepted. Two resampling procedures, cross-validation and the bootstrap, are introduced as simple statistical methods of validating soil-site models. These resampling methods provide a nearly unbiased estimate of the expected accuracy of a model. They are simple to computer program, and require no new data. The author recommends that soil scientists use a resam pling procedure for the initial validation of soil-site models prior to expensive field validation.
Promoters by IL-4 and CD40 e 1 and g Differential Regulation of Mouse Germline Ig

Before Ig class switching, RNA transcription through the speciﬁc S regions undergoing recombination is induced by cytokines and other activators that induce and direct switching. The resulting germline (GL) transcripts are essential for switch recombination. To understand the differential regulation of mouse IgG1 and IgE, we compared the promoters for GL g 1 and e transcripts. We addressed the question of why the promoter that regulates GL e transcription is more responsive to IL-4 than the g 1 promoter and also why GL e transcription is more dependent on IL-4 than is g 1 transcription. We found that the IL-4-responsive region of the GL e promoter is more inducible than that of the g 1 promoter, although each promoter contains a binding site for the IL-4-inducible transcription factor Stat6, located immediately adjacent to a binding site for a basic region leucine zipper (bZip) family protein. However, the arrangement and sequences of the sites differ between the e and g 1 promoters. The GL e promoter binds Stat6 with a 10-fold higher afﬁnity than does the g 1 promoter. Furthermore, the bZip elements of the two promoters bind different transcription factors, as the GL e promoter binds and is activated by AP-1, whereas the g 1 promoter binds and is activated by activating transcription factor 2. C/EBP b and C/EBP g also bind the g 1 bZip element, although they inhibit rather than activate transcription. However, inhibition of promoter activity by C/EBP b does not require the bZip element and may instead occur via inhibiting the activity of NF- k B. The Journal of Immunology, 2001, 167: 1522–1534. in
Fe 3 C-functionalized 3D nitrogen-doped carbon structures for electrochemical detection of hydrogen peroxide

Fe 3 C-functionalized three-dimensional (3D) porous nitrogen-doped graphite carbon composites (Fe 3 C/ NG) were synthesized via a facile solution-based impregnation and pyrolysis strategy using the commercially available melamine foam and FeCl 3 as precursors. The structural characterizations conﬁrmed that Fe 3 C nanoparticles with an average core size about 122 nm were assembled on the surface of the carbonized melamine foam (CMF) skeletons. The electrochemical measurements demonstrated the superior electrocatalytic activity of the advanced Fe 3 C/NG composite for hydrogen peroxide reduction reaction in 0.1 mol/L PBS electrolyte and the limit of detection of H 2 O 2 is estimated to be 0.035 mmol/L at a signal-to-noise ratio of 3 with a wide linear detection range from 50 l mol/L to 15 mmol/L ( R 2 = 0.999). Compared with the pure CMF, the Fe 3 C/NG exhibited higher catalytic activity, more stable response, lower detection limit, higher selectivity and a wider detection range, which could be attributed to the synergic effect between the two types of active sites from the iron carbide species and the nitrogen-doped graphite carbon. Meanwhile, the large surface area, high conductivity and the improved mass transport from the 3D porous material can also promote the electrochemical sensing performance. Moreover, the Fe 3 C/ NG-based electrochemical sensor showed high anti-inter-ference ability and stability for H 2 O 2 detection. Thus, the novel and low-cost Fe 3 C/NG composite may be a promising alternative to noble metals and offer potential applications in various types of electrochemical sensors, bioelectronic devices and catalysts.
A Periplasmic LolA Derivative with a Lethal Disulﬁde Bond Activates the Cpx Stress Response System (cid:1)

LolA accommodates the acyl chains of lipoproteins in its hydrophobic cavity and shuttles between the inner and outer membranes through the hydrophilic periplasm to place lipoproteins in the outer membrane. The LolA(I93C/F140C) derivative, in which Cys replaces Ile at position 93 and Phe at position 140, strongly inhibited growth in the absence of a reducing agent because of the lethal intramolecular disulﬁde bond between the two Cys residues. Expression of I93C/F140C was found to activate the Cpx two-component system, which responds to cell envelope stress. The inhibition of growth by I93C/F140C was partly suppressed by overproduction of LolCDE, which is an ATP-binding cassette transporter and mediates the transfer of lipoproteins from the inner membrane to LolA. A substantial portion of the oxidized form, but not the reduced one, of I93C/F140C expressed on LolCDE overproduction was recovered in the membrane fraction, whereas wild-type LolA was localized in the periplasm even when LolCDE was overproduced. Moreover, LolCDE overproduction stabilized I93C/F140C and therefore caused an increase in its level. Taken together, these results indicate that oxidized
Analysis of Topological Material Surfaces Analysis of Topological Material Surfaces

We provide a systematic analysis of the boundary condition for the edge state, which is a ubiquitous feature in topological phases of matter. We show how to characterize the boundary condition, and how the edge state spectrum depends on it, with several exam- ples, including 2d topological insulator and 3d Weyl semimetal. We also demonstrate the edge-of-edge state localized at the intersection of boundaries.
The Role of Supply Chain Integration in Sustainable Performance of Thai Manufacturing Organizations: A Mediation Effect of Supply Chain

- Sustainable performance is a serious concern for manufacturing organizations and a challenge for supply chain in the 21st century. Particularly a challenge is how to stimulate firms’ social and environmental attentiveness and put integrated activates into practice for sustainable performances. This study examine the role of supply chain integration in sustainable performance of Thai manufacturing firm with mediating role of supply chain performance. For the fulfillment of the objective of this research, the data was collected from the plant managers and supply chain managers via questioners. It is found that internal integration and logistic integration positively influence the sustainable performance of manufacturing organizations. Supply chain integration could enhance the supply chain performance of the firm that ultimately increases the sustainable performance of the organizations. The study offers a new empirical evidence for managerial decision and it can contribute valued perceptions for manufacturing firms in the strategy development regarding supply chain. However, this study used only internal integration and logistic integration, the other important element of supply chain such as customer integration and supplier integration, could be used by researchers for future research.
A General Framework for Unmet Demand Prediction in On-Demand Transport Services

Emerging on-demand transport services, such as Uber and GoGoVan, usually face the dilemma of demand supply imbalance, meaning that the spatial distributions of orders and drivers are imbalanced. Due to such imbalance, much supply resource is wasted while a considerable amount of order demand cannot be met in time. To address this dilemma, knowing the unmet demand in the near future is of high importance for service providers because they can dispatch their vehicles in advance to alleviate the impending demand supply imbalance, we develop a general framework for predicting the unmet demand in future time slots. Under this framework, we first evaluate the predictability of unmet demand in on-demand transport services and find that unmet demand is highly predictable. Then, we extract both static and dynamic urban features relevant to unmet demand from data sets in multiple domains. Finally, multiple prediction models are trained to predict unmet demand by using the extracted features. As demonstrated via experiments, the proposed framework can predict unmet demand in on-demand transport services effectively and flexibly.
New approach of friction model and identification for hydraulic system based on MAPSO-NMDS optimization Elman neural network

Hydraulic system smoothness is critical to product quality and position tracking. However, the nonlinear friction is an important factor causing unstable phenomenon of the hydraulic system when at low speed. Relevant research shows that the identified nonlinear friction has a large error with the actual friction force, which will bring a great challenge to design the friction compensation controller. Considering the difficulty of the friction model and identification, this article presents a new approach of friction model and identification for hydraulic system based on multi-agent particle swarm optimization–Nelder–Mead downhill simplex algorithm optimization Elman neural network. First, the nonlinear friction was established using the Elman neural network model. Then, a multi-agent particle swarm optimization–Nelder–Mead downhill simplex algorithm was proposed to search the nonlinear parameters of the Elman neural network model. Subsequently, the proposed algorithm was validated by complex nonlinear functions. Finally, the effectiveness of the Elman neural network model was demonstrated by the results from experiment. And comparison with the conventional LuGre friction model, the results show that the Elman neural network model predicts friction more accurately. This study provides the bases for designing the friction compensation controller.
Community-Based on Incarceration Among Gay Bisexual Stimulant-Using Homeless Adults.

This study was part of a randomized controlled trial designed to improve hepatitis knowledge and health promoting behaviors and subsequently decrease stimulant use and incarceration with 422 (G/B) homeless men between 18 and 46 years of age. Findings revealed that no signiﬁcant program differences on incarceration in the 4 months following the intervention. However, younger participants ( p = .010), and those with prior incarceration ( p = .001) were at greater risk for incarceration at 4 months. An additional factor associated with incarceration at 4 months included living on the street for at least 1 week ( p = .049).
Tn 5 Transposase with an Altered Speciﬁcity for Transposon Ends

Tn 5 is a composite bacterial transposon that encodes a protein, transposase (Tnp), required for movement of the transposon. The initial step in the transposition pathway involves speciﬁc binding of Tnp to 19-bp end recognition sequences. Tn 5 contains two different speciﬁc end sequences, termed outside end (OE) and inside end (IE). In Escherichia coli, IE is methylated by Dam methylase (IE ME ). This methylation greatly inhibits recognition by Tnp and greatly reduces the ability of transposase to facilitate movement of IE deﬁned transposons. Through use of a combinatorial random mutagenesis technique (DNA shufﬂing), we have isolated an IE ME -speciﬁc hyperactive form of Tnp, Tnp sC7v.2. 0, that is able to promote high levels of transposition of IE ME deﬁned transposons in vivo and in vitro while functioning at wild-type levels with OE transposons. This protein contains a critical glutamate-to-valine mutation at amino acid 58 that is responsible for this change in end speciﬁcity. It
Treating end user feedback seriously

Currently, patient satisfaction from NHS services is estimated with measures that may hardly relate to self-reported needs of patients or that use old data. Nonetheless, healthcare institutions depend on funding that is decided in part with the help of the ill-calculated patient satisfaction. As a result, patients’ actual best interest may be in conflict with the best interest of the evaluated NHS health organisations. Patients may receive suboptimal health services and lose trust in professionalism and intentions of doctors and health organisations that try to stick to performance targets. The reputation of medical professions may also drop and prompt health professionals to seek work elsewhere. Development of new organisational performance measurement tools from text data, the motive behind this study, can break the vicious cycle of distrust and improve the quality of healthcare by more accurately measuring patient satisfaction. The study involves processing of free-text online reviews of NHS GP services in England with deep learning to obtain a numeric representation of text data. Once text is transformed into numbers, two-ways fixed-effects regressions were carried out to see if there is a statistically significant correlation between how patients write about individual GP practices and their numeric evaluations of the GP services. Initial findings indicate that written reviews can be used as a predictor of patient satisfaction, and may be used to obtain real-time insights about whether and why patients are happy and/or unhappy about their GP service experience.
Metabolism of Monoterpenes1 METABOLIC FATE OF (+)-CAMPHOR IN SAGE (SAL VIA OFFICINALIS)

The bicyclic monoterpene ketone (+)-camphor undergoes lactonization to 1,2-campholide in mature sage (Sah'ia officinalis L.) leaves followed by conversion to the jO-Dfglucoside-6-0-glucose ester of the corresponding hydroxy acid (l-carboxymethyl-3-hydroxy-2,2,3-trimethyl cyclopen-tane). Analysis of the disposition of (+G3Hjcamphor applied to midstem leaves of intact flowering plants allowed the kinetics of synthesis of the bis-glucose derivative and its transport from leaf to root to be determined, and pve strong indication that the transport derivative was subsequently metabolized in the root. Root extracts were shown to possess j@ glucosidase and acyl glucose esterase activities, and studies with (+)- 1,2[U-4"Ccampholide as substrate, using excised root segments, revealed that the terpenoid was converted to lipid materials. Localization studies confirmed the radiolabeled lipids to reside in the membranous fractions of root extracts, and analysis of this material indicated the presence of labeled phytosterols and labeled fatty acids (C,4 to C20) of acyl lipids. and the acyl lipids and phytosterols and isoprenoid biosynthetic pathways. Monoterpene catabolism thus appears to represent a salvage mechanism for recycling mobile carbon from senescing oil glands on the leaves to the roots.