bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALYSIS OF A DAMPED FRACTAL SYSTEM USING THE ANCIENT CHINESE ALGORITHM AND THE TWO-SCALE FRACTAL DIMENSION TRANSFORM
Authors: ELíAS-ZÚÑIGA ALEX , MARTíNEZ-ROMERO OSCAR , TREJO DANIEL OLVERA , PALACIOS-PINEDA LUIS MANUEL
Published: August 2022

This paper investigates the applicability of the ancient Chinese algorithm jointly with the two-scale fractal dimension transform to find the frequency–amplitude relationship of fractal equations of motion with and without damping terms. Analytical results show that for a fractal equation of motion without damping terms, the oscillation amplitudes do not exhibit decaying effects. However, when damping terms are included, the fractal parameter tends to shift the decaying oscillation amplitudes that decrease faster with time for fractal values less than one. This paper provides an efficient tool for finding the amplitude–frequency relationship of damped fractal oscillators. To illustrate the solution process, the steady-state solution of the fractal equation of motion that arises in plasma physics is derived. The proposed approach elucidates the applicability of He’s formulation jointly with the two-scale fractal calculus to find the frequency–amplitude of fractal systems with and without damping terms.
Dilation, functional model and a complete unitary invariant for C.0Γn-contractions
Authors: Pal Sourav
Published: August 2022

A commuting tuple of operators [Formula: see text], defined on a Hilbert space [Formula: see text], for which the closed symmetrized polydisc [Formula: see text] is a spectral set, is called a [Formula: see text]-contraction. A [Formula: see text]-contraction is said to be pure or [Formula: see text] if [Formula: see text] is [Formula: see text], that is, if [Formula: see text] strongly as [Formula: see text]. We show that for any [Formula: see text]-contraction [Formula: see text], there is a unique operator tuple [Formula: see text] that satisfies the operator identities [Formula: see text] This unique tuple is called the fundamental operator tuple or [Formula: see text]-tuple of [Formula: see text]. With the help of the [Formula: see text]-tuple, we construct an operator model for a [Formula: see text] [Formula: see text]-contraction and show that there exist [Formula: see text] operators [Formula: see text] such that each [Formula: see text] can be represented as [Formula: see text]. We find an explicit minimal dilation for a class of [Formula: see text] [Formula: see text]-contractions whose [Formula: see text]-tuples satisfy a certain condition. Also, we establish that the [Formula: see text]-tuple of [Formula: see text] together with the characteristic function of [Formula: see text] constitutes a complete unitary invariant for the [Formula: see text] [Formula: see text]-contractions. The entire program is an analog of the Sz.-Nagy–Foias theory for [Formula: see text] contractions.
A new construction of shearlets
Authors: Ghaderihasab Pooran , Ahmadi Ahmad
Published: August 2022

In order to achieve optimally sparse approximations of signals exhibiting anisotropic singularities, the shearlet systems that are systems of functions generated by one generator with dilation, shear transformation and translation operators applied to it were introduced. In this paper, we will construct the shearlet systems that are not only Parseval frames for [Formula: see text] but they are also obtained from an [Formula: see text]-MRA associated with wavelet multiresolution, and by using this approach, we obtain the corresponding filters for these systems. For this purpose, the tensor product of the corresponding wavelet scaling function and a compact support bump function is used to construct the scaling function associated with the shearlet.
Managing Technological Innovation Capabilities to Align Exploration and Exploitation with Technological Changes
Authors: Erzurumlu S. Sinan , Smith Nathan
Published: August 2022

Firms that operate in high-velocity markets must configure and utilize diverse technological innovation capabilities (TICs). TICs provide the firm with technological strength and adaptability to manage technological changes with respect to demand changes on the customer value trajectory. In this paper, we examine the configuration of a high tech firm’s TICs involving R&D, manufacturing and marketing capabilities to develop technology exploring or market exploiting activities in response to shifts in the customer value trajectory. We analyze the cases of micro, electrical, mechanical systems (MEMS) accelerometer innovators, and identify strategic configuration of TICs that has been necessary to trace the customer value trajectory with technological changes. We further show how the stability of the customer value trajectory plays a role for the firm in market transition to configure and utilize its TICs for exploring or exploiting the market. Based on our findings, we offer a managerial decision-making framework regarding strategic management of TICs with respect to the customer value trajectory in high-velocity markets.
Potential of phthalocyanine on streptozotocin-induced diabetic rats: An initiative of dye in substitution of therapeutics
Authors: Govardhane Sharayu , Shende Pravin
Published: August 2022

Type 1 diabetes mellitus, is one of the severe chronic metabolic diseases with severe worldwide complications due to increased levels of glucose affecting many organ functionalities. Antioxidant properties reduce the free radicals and inhibit the oxidation that promotes cellular development in many conditions such as diabetes, Alzheimer’s disease and cardiovascular disorders. Phthalocyanine is a large blue colored aromatic compound with high potential of anti-oxidant ability owing to the presence of porphyrazine ring units. The present study has aimed at examining the potential effect of phthalocyanine on the streptozotocin-induced diabetic model over 28 days. For the study, the animals were assigned into 4 groups: control, diabetic, phthalocyanine (10 [Formula: see text]g/kg/day) treated diabetic group and phthalocyanine (20 [Formula: see text]g/kg/day) treated diabetic group. After the induction of diabetes using streptozotocin (53 mg/kg body weight), phthalocyanine (10 [Formula: see text]g/kg/day) and phthalocyanine (20 [Formula: see text]g/kg/day) were given daily for 28 days and the blood glucose level was checked on 7th, 14th, 21st and 28th day. A significant reduction in blood glucose within the period on the 28th day with increase in body weight was observed. Phthalocyanine also showed a decrease in the total protein content and blood urea nitrogen with improved oxidative stress parameters. The histopathological analyses displayed improvement in pancreatic structure with basal rounded nuclei and well-defined boundaries normal acini with a phthalocyanine dose (10 [Formula: see text]g/kg). It was concluded that phthalocyanine at the dose of 10 [Formula: see text]g/kg presented anti-diabetic and anti-hyperlipidemic actions with protective effect to the pancreatic [Formula: see text]-cell within 28 days.
Distance Minimizing-Based Data-Driven Computational Plasticity Method with Fixed Dataset
Authors: Zheng Zhangcheng , Zhang Hongwu , Ye Hongfei , Zheng Yonggang
Published: August 2022

A data-driven computational plasticity method based on the distance minimizing framework is proposed in this paper. In this method, the internal variables in conventional plasticity are abandoned and a fixed dataset considering path-dependent behaviors of materials is constructed. With the fixed dataset, a stress correspondence method is developed to compute the plastic strain of every integration point at each load step, and a data-driven classification model for yielding is constructed to rapidly determine the yield status of each point in the method. Moreover, a symmetric mapping method is developed to accurately determine the stress–strain state of the integration point under unloading or inverse loading conditions. Several representative examples are presented to show the capability of the proposed method. Numerical results of two- and three-dimensional truss structures and three-dimensional continuum bodies demonstrate the high efficiency and accuracy of the proposed data-driven computational plasticity method.
Recent Progress of Smart Nano-Based Biosensors and their Applications in Biomedicine
Authors: Hasanzadeh Akbar , Azmand Hojjat Rostami , Ebadati Arefeh , Nourizadeh Helena , Hashemzadeh Iman , Noori Hamid , Seo Sang-Woo , Aref Amir R. , Karimi Mahdi
Published: August 2022

Recent advances in miniaturized nano-based devices are rapidly extending the boundaries of biomedical technologies, particularly biosensors. Highly selective biosensors with the ability to simultaneously detect multiple targets were developed in recent years. The most eye-catching classifications of such biosensors coupled with the emergence of stimuli-responsive and CRISPR/Cas-sensitive systems. Furthermore, attractive features of wearable and implantable biosensors have led to the design of portable, remote controllable diagnostic systems for tackling healthcare challenges in every part of the world, especially in places with limited access to clinical resources. Nevertheless, there are still some barriers to widespread applications of biosensors due mainly to their high costs and the lack of a single biosensing device for highly selective targeting of multiple analytes. Herein, we review the latest developments in biomedical technologies with a focus on biosensors including smart stimuli-responsive, CRISPR/Cas-sensitive, wearable, and implantable biosensors to spark innovations in this field.
PECVD of Vertical Graphene: Local Plasma or Nonlocal Plasma?
Authors: Xiong Fangzhu , Qian Fengsong , Sun Jie , Guo Weiling , Li Longfei , Xie Yiyang , Du Zaifa , Dong Yibo , Wang Le , Xu Chen
Published: August 2022

Using the plasma-enhanced chemical vapor deposition method, we grow vertical graphene thin films onto SiO2/Si substrates, which is a special format of graphene composed of numerous macroscopically uniformly distributed graphene flakes approximately vertically arranged. The growth parameters, including the growth temperature, growth time and plasma power, are systematically studied and optimized. Most importantly, the function of plasma has been revealed. In the same deposition machine, we have altered the plasma electrode and heater configurations, and found that the vertical graphene can only grow in local plasma environment. That is, the samples have to be well immersed in the plasma sheath electric field. In this way, the vertical growth of graphene and the local enhancement of electric field can form a positive feedback loop, resulting in the continuous growth of vertical graphene. This experiment clarifies the function of plasma electric field in the vertical graphene growth, and can offer hints for the growth of other vertical two-dimensional materials as well. The vertical graphene films are scalable, transfer-free and lithographically patternable, which is compatible with standard semiconductor processing and promising for optoelectronic applications. We have characterized the optical properties of the as-grown vertical graphene films, where a nearly zero transmittance is observed for 1100–2600[Formula: see text]nm wavelengths, indicating a superstrong absorption in the black colored vertical graphene.
Stimulated Raman scattering microscopy on biological cellular machinery
Authors: Huang Jing , Ji Minbiao
Published: August 2022

Benefiting from the developments of advanced optical microscopy techniques, the mysteries of biological functions at the cellular and subcellular levels have been continuously revealed. Stimulated Raman scattering (SRS) microscopy is a rapidly growing technique that has attracted broad attentions and become a powerful tool for biology and biomedicine, largely thanks to its chemical specificity, high sensitivity and fast image speed. This review paper introduces the principles of SRS, discusses the technical developments and implementations of SRS microscopy, then highlights and summarizes its applications on biological cellular machinery and finally shares our visions of potential breakthroughs in the future.
On Symmetric Rectilinear Partitioning
Authors: Yaşar Abdurrahman , Balin Muhammed Fati̇h , An Xiaojing , Sancak Kaan , Çatalyürek Ümit V.
Published: August 2022

Even distribution of irregular workload to processing units is crucial for efficient parallelization in many applications. In this work, we are concerned with a spatial partitioning called rectilinear partitioning (also known as generalized block distribution). More specifically, we address the problem of symmetric rectilinear partitioning of two dimensional domains, and utilize sparse matrices to model them. By symmetric, we mean both dimensions (i.e., the rows and columns of the matrix) are identically partitioned yielding a tiling where the diagonal tiles (blocks) will be squares. We first show that the optimal solution to this problem is NP-hard, and we propose four heuristics to solve two different variants of this problem. To make the proposed techniques more applicable in real life application scenarios, we further reduce their computational complexities by utilizing effective sparsification strategies together with an efficient sparse prefix-sum data structure. We experimentally show the proposed algorithms are efficient and effective on more than six hundred test matrices/graphs.
Program adverbs and Tlön embeddings
Authors: Li Yao , Weirich Stephanie
Published: August 2022

Free monads (and their variants) have become a popular general-purpose tool for representing the semantics of effectful programs in proof assistants. These data structures support the compositional definition of semantics parameterized by uninterpreted events, while admitting a rich equational theory of equivalence. But monads are not the only way to structure effectful computation, why should we limit ourselves?

In this paper, inspired by applicative functors, selective functors, and other structures, we define a collection of data structures and theories, which we call program adverbs, that capture a variety of computational patterns. Program adverbs are themselves composable, allowing them to be used to specify the semantics of languages with multiple computation patterns. We use program adverbs as the basis for a new class of semantic embeddings called Tlön embeddings. Compared with embeddings based on free monads, Tlön embeddings allow more flexibility in computational modeling of effects, while retaining more information about the program's syntactic structure.
Introduction and elimination, left and right
Authors: Ostermann Klaus , Binder David , Skupin Ingo , Süberkrüb Tim , Downen Paul
Published: August 2022

Functional programming language design has been shaped by the framework of natural deduction, in which language constructs are divided into introduction and elimination rules for
producers
of values. In sequent calculus-based languages, left introduction rules replace (right) elimination rules and provide a dedicated sublanguage for
consumers
of values. In this paper, we present and analyze a wider design space of programming languages which encompasses four kinds of rules: Introduction and elimination, both left and right. We analyze the influence of rule choice on program structure and argue that having all kinds of rules enriches a programmer’s modularity arsenal. In particular, we identify four ways of adhering to the principle that ”the structure of the program follows the structure of the data“ and show that they correspond to the four possible choices of rules. We also propose the principle of
bi-expressibility
to guide and validate the design of rules for a connective. Finally, we deepen the well-known dualities between different connectives by means of the proof/refutation duality.
Analyzing binding extent in 3CPS
Authors: Quiring Benjamin , Reppy John , Shivers Olin
Published: August 2022

To date, the most effective approach to compiling strict, higher-order functional languages (such as OCaml, Scheme, and SML) has been to use whole-program techniques to convert the program to a first-order monomorphic representation that can be optimized using traditional compilation techniques. This approach, popularized by MLton, has limitations, however. We are interested in exploring a different approach to compiling such languages, one that preserves the higher-order and polymorphic character of the program throughout optimization. To enable such an approach, we must have effective analyses that both provide precise information about higher-order programs and that scale to larger units of compilation. This paper describes one such analysis for determining the
extent
of variable bindings. We classify the extent of variables as either
register
(only one binding instance can be live at any time),
stack
(the lifetimes of binding instances obey a LIFO order), or
heap
(binding lifetimes are arbitrary). These extents naturally connect variables to the machine resources required to represent them. We believe that precise information about binding extents will enable efficient management of environments, which is a key problem in the efficient compilation of higher-order programs.

At the core of the paper is the 3CPS intermediate representation, which is a factored CPS-based intermediate representation (IR) that statically marks variables to indicate their binding extent. We formally specify the management of this binding structure by means of a small-step operational semantics and define a static analysis that determines the extents of the variables in a program. We evaluate our analysis using a standard suite of SML benchmark programs. Our implementation gets surprisingly high yield and exhibits scalable performance. While this paper uses a CPS-based IR, the algorithm and results are easily transferable to other λ-calculus IRs, such as ANF.
Evaluating the Cybersecurity Risk of Real-world, Machine Learning Production Systems
Authors: Bitton Ron , Maman Nadav , Singh Inderjeet , Momiyama Satoru , Elovici Yuval , Shabtai Asaf
Published: August 2022

Although cyberattacks on machine learning (ML) production systems can be harmful, today, security practitioners are ill-equipped, lacking methodologies and tactical tools that would allow them to analyze the security risks of their ML-based systems. In this article, we perform a comprehensive threat analysis of ML production systems. In this analysis, we follow the ontology presented by NIST for evaluating enterprise network security risk and apply it to ML-based production systems. Specifically, we (1) enumerate the assets of a typical ML production system, (2) describe the threat model (i.e., potential adversaries, their capabilities, and their main goal), (3) identify the various threats to ML systems, and (4) review a large number of attacks, demonstrated in previous studies, which can realize these threats. To quantify the risk posed by adversarial machine learning (AML) threat, we introduce a novel scoring system that assigns a severity score to different AML attacks. The proposed scoring system utilizes the analytic hierarchy process (AHP) for ranking—with the assistance of security experts—various attributes of the attacks. Finally, we developed an extension to the MulVAL attack graph generation and analysis framework to incorporate cyberattacks on ML production systems. Using this extension, security practitioners can apply attack graph analysis methods in environments that include ML components thus providing security practitioners with a methodological and practical tool for both evaluating the impact and quantifying the risk of a cyberattack targeting ML production systems.
Approximating (
k,ℓ
)-Median Clustering for Polygonal Curves
Authors: Buchin Maike , Driemel Anne , Rohde Dennis
Published: August 2022

In 2015, Driemel, Krivošija, and Sohler introduced the
k,ℓ
-median clustering problem for polygonal curves under the Fréchet distance. Given a set of input curves, the problem asks to find
k
median curves of at most ℓ vertices each that minimize the sum of Fréchet distances over all input curves to their closest median curve. A major shortcoming of their algorithm is that the input curves are restricted to lie on the real line. In this article, we present a randomized bicriteria-approximation algorithm that works for polygonal curves in ℝ

d

and achieves approximation factor (1+ɛ) with respect to the clustering costs. The algorithm has worst-case running time linear in the number of curves, polynomial in the maximum number of vertices per curve (i.e., their complexity), and exponential in
d
, ℓ, 1/ɛ and 1/δ (i.e., the failure probability). We achieve this result through a shortcutting lemma, which guarantees the existence of a polygonal curve with similar cost as an optimal median curve of complexity ℓ, but of complexity at most 2ℓ -2, and whose vertices can be computed efficiently. We combine this lemma with the superset sampling technique by Kumar et al. to derive our clustering result. In doing so, we describe and analyze a generalization of the algorithm by Ackermann et al., which may be of independent interest.
Open problems column
Authors: Gasarch William
Published: August 2022

This Issue's Column!
This issue's Open Problem Column is by William Gasarch, Emily Kaplitz, and Erik Metz.
Guest column: A panorama of counting problems the decision version of which is in P
3
Authors: Bakali Eleni , Chalki Aggeliki , Göbel Andreas , Pagourtzis Aris , Zachos Stathis
Published: August 2022

Since Valiant's seminal work, where the complexity class #P was defined, much research has been done on counting complexity, from various perspectives. A question that permeates many of these efforts concerns the approximability of counting problems, in particular which of them admit an efficient approximation scheme (
fpras
). A counting problem (a function from Σ
*
to N) that admits an
fpras
must necessarily have an easy way to decide whether the output value is nonzero. Having this in mind, we focus our attention on classes of counting problems, the decision version of which is in P (or in RP). We discuss structural characterizations for classes of such problems under various lenses: Cook and Karp reductions, path counting in non-deterministic Turing machines, approximability and approximation-preserving reductions, easy decision by randomization, descriptive complexity, and interval-size functions. We end up with a rich landscape inside #P, revealing a number of inclusions and separations among complexity classes of easy-to-decide counting problems.
Size-based scheduling vs fairness for datacenter flows
Authors: Roberts James , Rossi Dario
Published: August 2022

Contrary to the conclusions of a recent body of work where approximate shortest remaining processing time first (SRPT) flow scheduling is advocated for datacenter networks, this paper aims to demonstrate that imposing fairness remains a preferable objective. We evaluate abstract queuing models by analysis and simulation to illustrate the non-optimality of SRPT under the reasonable assumptions that datacenter source-destination flows occur in batches and bursts and not, as usually assumed, individually at the instants of a Poisson process. Results for these models have significant implications for the design of bandwidth sharing strategies for datacenter networks. In particular, we propose a novel "virtual fair scheduling" algorithm that enforces fairness between batches and is arguably simple enough to be implemented in high speed devices.
DOLL
Authors: Jiang Harry , Zhang Xiaoxi , Joe-Wong Carlee
Published: August 2022

Most large-scale ML implementations scale to large amounts of data by utilizing multiple servers or virtual machines (VMs) that iteratively compute model updates on local data that are periodically synchronized. Due to the complexity of managing the resulting computing infrastructure, many companies run their ML jobs on external cloud providers' servers. However, cloud resources can be expensive, particularly for large ML jobs with long runtimes.

A particularly popular method to limit the costs of training ML jobs is to utilize preemptible cloud instances. These may be interrupted at the cloud provider's discretion, but they are significantly (up to 90%) cheaper than conventional on-demand instances. Most studies of these ML methods, however, assume the availability of large datasets at training time. In practice, training data may arrive at irregular intervals and models may be trained online as new data samples arrive, e.g., when monitoring data from IoT sensors. While some software frameworks like Apache Kafka can feed online data arrivals to ML algorithms, they provide little insight into the resulting costs of ML training. We extend prior work on provisioning preemptible instances to analyze available pools of data in order to run online ML on incoming datastreams, which presents new challenges due to the need to carefully handle data arrivals. We design, analyze, and optimize DOLL, which to the best of our knowledge is the first system that provides provable performance guarantees for Distributed OnLine Learning over preemptible instances.

Research Challenges and Our Contributions: When pools of data are readily available, the bottleneck to distributed ML training often lies in the time required for each VM to compute its model updates. In our scenario, however, the arrival rate of incoming data may also bottleneck data processing. An intuitive strategy would then be for each VM to process each data point as it arrives. However, since arrivals at different VMs may not be coordinated, synchronizing the model parameters at each VM between data arrivals may introduce additional delays, while asynchronous SGD methods can lead to slow convergence [1]. DOLL uses a batching and grouping process to limit the synchronization delay, which naturally realizes traditional mini-batch SGD so as to provide provable model convergence guarantees.

Handling online data arrivals becomes particularly challenging when we use preemptible instances to compute model updates. Existing methods utilizing preemptible instances for ML jobs largely focus on mitigating training interruptions [2] and their effects on model convergence [3]. When used on datastreams, we face an additional challenge of interruptions pausing the data arrival process, which impedes the rate at which we can compute model updates and thus model convergence. Thus, one should ensure that preemptions do not happen "too often," e.g., by computing some updates on on-demand instances. Our work is the first to optimize the number of preemptible VMs used and demonstrate that we can meet ML convergence guarantees.
Sojourn Time Minimization of Successful Jobs
Authors: Yao Yuan , Paolieri Marco , Golubchik Leana
Published: August 2022

Due to a growing interest in deep learning applications [5], compute-intensive and long-running (hours to days) training jobs have become a significant component of datacenter workloads. A large fraction of these jobs is often exploratory, with the goal of determining the best model structure (e.g., the number of layers and channels in a convolutional neural network), hyperparameters (e.g., the learning rate), and data augmentation strategies for the target application. Notably, training jobs are often terminated early if their learning metrics (e.g., training and validation accuracy) are not converging, with only a few completing successfully.

For this motivating application, we consider the problem of scheduling a set of jobs that can be terminated at predetermined checkpoints with known probabilities estimated from historical data. We prove that, in order to minimize the time to complete the first K successful jobs on a single server, optimal scheduling does not require preemption (even when preemption overhead is negligible) and provide an optimal policy; advantages of this policy are quantified through simulation.

Related Work. While job scheduling has been investigated extensively in many scenarios (see [6] and [2] for a survey of recent result), most policies require that the cost of waiting times of each job be known at scheduling time; in contrast, in our setting the scheduler does not know which job will be the K-th successful job, and sojourn times of subsequent jobs do not contribute to the target metric.

For example, [4, 3] minimize makespan (i.e., the time to complete all jobs) for known execution times and waiting time costs; similarly, Gittins index [1] and SR rank [7] minimize expected sojourn time of all jobs, i.e., both successfully completed jobs and jobs terminated early. Unfortunately, scheduling policies not distinguishing between these two types of jobs may favor jobs where the next stage is short and leads to early termination with high probability, which is an undesirable outcome in our applications of interest.
Optimized numerical inverse Laplace transformation
Authors: Horvath Illes , Meszaros Andras , Telek Miklos
Published: August 2022

Among the numerical inverse Laplace transformation (NILT) methods, those that belong to the Abate-Whitt framework (AWF) are considered to be the most efficient ones currently. It is a characteristic feature of the AWF NILT procedures that they are independent of the transform function and the time point of interest.

In this work we propose an NILT procedure that goes beyond this limitation and optimize the accuracy of the NILT utilizing also the transform function and the time point of interest.
On Quantum Algorithms for Random Walks in the Nonnegative Quarter Plane
Authors: Kalantzis Vasileios , Squillante Mark S. , Ubaru Shashanka , Horesh Lior
Published: August 2022

It is well known that strong connections exist between random walks (RWs) in the nonnegative quarter plane and the mathematical performance modeling, analysis and optimization of computer systems and communication networks. Examples include adaptive threshold-based load balancing in concert with affinity scheduling (e.g., [16, 10]), scheduling parallel jobs on parallel computer systems (e.g., [15]), and asymptotic scalabilty in wireless and linear loss networks (e.g., [9]).
GranularNF
Authors: Wu Ziyan , Cui Tianming , Narayanan Arvind , Zhang Yang , Lu Kangjie , Zhai Antonia , Zhang Zhi-Li
Published: August 2022

In this paper, we consider the challenges that arise from the need to scale virtualized network functions (VNFs) at 100 Gbps line speed and beyond. Traditional VNF designs are monolithic in state management and scheduling: internally maintaining all states and operations associated with them. Without proper design considerations, it suffers from limitations when scaling at 100 Gbps link speed and beyond: the inability of efficient utilization of the cache because of the contention due to the frequent control plane activities, computational/memory-intensive tasks taking up CPU times, shares states causing the synchronization among the cores.

We address these limitations by arguing for the need to granularly decompose a VNF into data/control components that are co-located within a server but can be independently scaled among the cores. To realize the approach, we design a "serverless" programming framework with novel abstraction to optimize the data components that must process packets at the line speed, reduce the contention of the data states and enable run-time scheduling of different components for improved resource utilization. The abstractions, combined with the runtime system that we design, help NFV developers focus on the logic and correctness of VNF programming without worrying about how VNFs may be scaled in or out. We evaluate our platform by comparing it with monolithic approaches using different workloads and by analyzing its advantages of separation on scalability, performance determinism, and feature velocity.
Nanostructure Quantification of Hard Carbon Electrodes through Advanced HRTEM Image Analysis
Authors: Li Jiaqi , Ouyang Huping , Wang Jingkun , Li Jie , Zhang Hongliang
Published: August 2022

The currently remaining uncertainties on nanostructure has severely hindered the optimal design of hard carbon electrodes. HRTEM characterizations allow us to carry out structural measurements at the atomic level, however, extracting physically meaningful and statistically robust data from HRTEM images is not an easy process. In this work, intelligent fringe analysis and Gabor filtering algorithm were combined to reduce subjective bias and improve statistical reliability. Fringe orientation was described by nematic symmetry of second-order statistics. As a representative, detailed structural analysis of sucrose-derived hard carbon prepared at different heat treatment temperatures (HTTs) was performed. Advanced HRTEM image analysis reveals that the nanostructural evolution of hard carbon is manifested in several aspects, involving the growth and flattening of fringes, enhancement of ordering alignment, increase of stacking, and development of symmetry. More importantly, these structural parameters were quantitatively analyzed in detail. The structural parameters obtained by HRTEM are consistent with similar parameters obtained by other techniques such as XRD. This work provides an unprecedented quantitative insight into the nanostructural trends of hard carbon, with potential to aid researchers in elucidating the structure-property relationships of carbon electrodes
Numerical Simulation for Improving Coating Homogeneity of High-Speed Tin Plating System
Authors: Zhao Yinghai , Mo Zhiying , Wang Zhenwen , Li Ning , Xu Yanling , Li Deyu
Published: August 2022

The influence of electrodeposition coating uniformity is complex; in essence, coating thickness depends on the potential distribution on the cathode surface, which is jointly affected by geometric and electrochemical factors. In a realistic high-speed tin plating production process, the edge effect has always been a vital problem to the homogeneity of electrodeposition coatings. Due to the complexity of production equipment and the high costs of spot experiments, modeling and simulation have become promising ways to study how to improve the uniformity of coatings. In this paper, we proposed reasonable model simplification strategies in the high-speed tin electrodeposition process and studied the influence of anode arrangement and auxiliary equipment on the uniformity of tin plating coating based on COMSOL Multiphysics. The results showed that changing the relative positions of cathode and anode cannot make the coating evenly distributed while adding specific auxiliary devices at appropriate locations would helpfully solve the uneven coating problem caused by edge effects. The research not only aims at a high-speed tin plating system but also has a great reference with any plate-type cathode electrodeposition for improving the homogeneity of coatings.
Case studies in neuroscience: reversible signatures of edema following electric and piezoelectric craniotomy drilling in macaques
Authors: Boshra Rober , Eradath Manoj , Dougherty Kacie , Wu Bichan , Morea Britney M. , Harris Michael , Pinsk Mark A. , Kastner Sabine
Published: August 2022

Close examination of structural MRI in eight nonhuman primates following craniotomy surgeries for intracranial electrophysiology highlights a prevalence of hyperintensities on T2-weighted scans following surgeries conducted using electric and piezoelectric drills, but not when using mechanical, hand-operated drills. We interpret these anomalies as edema of neural tissue that resolved 2–3 wk postsurgery. This finding is especially of interest as electrophysiological recordings from compromised tissue may directly influence the integrity of collected data immediately following surgery.
Contrasting dose-dependent effects of acute intravenous methamphetamine on lateral hypothalamic extracellular glucose dynamics in male and female rats
Authors: Kuebler Isabel R. K. , Jolton Joshua A. , Hermreck Chase , Hubbard Nicholas A. , Wakabayashi Ken T.
Published: August 2022

Enzyme-linked glucose biosensors were used to monitor lateral hypothalamic (LH) extracellular fluctuations during nondrug stimuli and intravenous methamphetamine injections in drug-naive awake male and female rats. Second-scale glucose changes occurred after nondrug stimuli, differing by modality and sex. Robust minute-scale decreases followed most methamphetamine injections. Sex differences at the minute-scale indicate female central glucose regulation is more sensitive to methamphetamine effects. We discuss likely mechanisms underlying these fluctuations, and their implications in methamphetamine use disorder.
Sensory signals of unloading in insects are tuned to distinguish leg slipping from load variations in gait: experimental and modeling studies
Authors: Harris Christian M. , Szczecinski Nicholas S. , Büschges Ansgar , Zill Sasha N.
Published: August 2022

Decreases in loading of legs are important in the regulation of posture and walking in both vertebrates and invertebrates. Recordings of activities of tibial campaniform sensilla, which encode forces in insects, showed that their responses are specifically tuned to detect force decreases at the end of the stance phase of walking or when a leg slips. These results have been reproduced in a mathematical model of the receptors and also have potential applications in robotics.
Using a chopping task to compare expert and competent motor memory
Authors: Nepotiuk Anastasia H. , Brown Liana E.
Published: August 2022

From the lab, a comparison of expert chefs to competent home cooks on a defined chopping task shows that vulnerability of motor memory to interference changes with expertise.
Continuum Approximation Model for Transit Service Design with Stochastic Demand
Authors: Xia Liang , Li Haibo , Fan Yingfei , Jiang Xinguo
Published: August 2022

Travel demand is commonly predefined as a constant during the planning period in transit service design, but it varies daily with many factors, for example, weather, vacation, and social activity. Under the uncertain demand, the transit system operates in two states, that is, unsaturation and saturation, distinguished by whether or not the capacity of transit vehicle satisfies the possible demand. Thus, we propose a continuum approximation (CA) model for transit service design, including headway and station location, to account for the effects of the stochastic demand via a penalty cost, a service-reliability constraint, and equilibrium. The penalty cost is utilized to describe the saturation state. The service-reliability constraint is applied to ensure the robustness of the transit system. The equilibrium is introduced to allocate the household location where trip demand is generated in a corridor. Furthermore, we build a bilevel framework to find the solutions to the proposed model. In the numerical experiment, the proposed model is applied in the impact analyses of the service-reliability constraint, as well as the sensitivity analyses of the household numbers and value of time. The impact analyses indicate that the transit service design integrated with the effect of housing location choice is necessary under the stochastic demand. The sensitivity analyses show that the number of households and the value of time play a significant role in the performance of transit systems accounting for service reliability. The proposed model and findings serve to improve the design of the transit system under stochastic demand.
Adsorption of Indigo Carmine onto Chemically Activated Carbons Derived from the Cameroonian Agricultural Waste Garcinia cola Nut Shells and Desorption Studies
Authors: Tiotsop Kuete Idris-Hermann , Tchuifon Tchuifon Raoul Donald , Bopda Aurelien , Sadeu Ngakou Christian , Nche George Ndifor-Angwafor , Gabche Anagho Solomon
Published: August 2022

In the quest for a sustainable environment and clean water resources, the efficacy of activated carbons synthesized from Garcinia cola nut shells impregnated with KOH (CBK1/1) and ZnCl2 (CBZ1/1) for the adsorption of indigo carmine (IC) dye was studied using the batch technique. The prepared activated carbons were characterized using iodine number, elemental analysis, scanning electron microscopy (SEM), FTIR spectroscopy, powder X-ray diffraction (XRD), TGA/DTA, Boehm titration, and pH at point of zero charge. The elemental analysis showed a high percentage of carbon in both activated carbons (ACs). FTIR and Boehm titration analysis indicated the presence of several functional groups on the surfaces of both ACs which could influence the adsorption of IC. The primary adsorption mechanisms involved electrostatic interaction, hydrogen bonds formation, and π−π interactions. Maximum adsorption capacity values obtained using the Fritz–Schlunder III three-parameter model were 19.019 mg·g−1 and 18.299 mg·g−1 for CBK1/1 and CBZ1/1, respectively. The Fritz–Schlunder model exponent mFS of value less than 1 showed that the adsorption of IC by the ACs occurred on heterogeneous surfaces. Positive values of ∆Q obtained by the linear and nonlinear forms of the Temkin model indicate the exothermic character of the adsorption process.
Economics of Sesame and Its Use Dynamics in Ethiopia
Authors: Sirany Teshome , Tadele Esubalew
Published: August 2022

Ethiopia’s oilseed industry makes a major contribution to foreign exchange revenues. Ethiopia’s three main oilseed crops (sesame, soybean, and Niger seed) account for about 20% of the country’s total agricultural export profits, second only to coffee. Even though Ethiopia is one of the world’s largest producers and exporters of sesame seeds, the country is facing increasing supply and demand restrictions. This paper begins with an examination of one of the most prominent oil crops in the country. It is a highly adaptable crop that may be used for anything from subsistence to commercial output. We established a comprehensive scientific understanding of the crop using a systematic review of the current literature and deductive logical reasoning that can be used to inform future research and policies. Various exclusion and inclusion criteria were used to filter the most notable findings. Millions of growers and other market participants are employed throughout the oilseed value chain. Reduced sesame productivity, pests and diseases, and limited access to modern technologies are all severe supply-side constraints. On the demand side, traders and market distortion, as well as an artificially higher home price and the ease with which unskilled labor can enter the market, are all factors. Other demand-side constraints include worldwide price volatility, a highly concentrated export market, and intense global competition. Ethiopia’s sesame seed development potential is being severely hampered by these restrictions. If farmers, dealers, and the government do not address these issues strategically, the country may soon lose its competitiveness in the global sesame seed market. This will contribute to Ethiopia’s ongoing discussion about how to better inform private and public sector policies and investments to increase sesame production, transform agriculture, improve nutrition and food systems, and be able to ease supply- and demand-side restrictions. In a nutshell, an increased area under cultivation combined with best agronomic practices could boost sesame production. Farmers, policymakers, researchers, and other stakeholders must thus intervene to enhance sesame production. Future studies should concentrate on how to boost sesame output in farmers’ fields while following appropriate sesame production technology and agronomic principles.
Evaluation of the Effects of Multifocal Intraocular Lens Oculentis LENTIS Mplus LS-313 MF30 on Visual Performance in Patients Affected by Bilateral Cataract and Treated with Phacoemulsification
Authors: Nuzzi R. , Tripoli F. , Ghilardi A.
Published: August 2022

Background. The purpose of this study was to evaluate the visual results and patients’ satisfaction with surgical treatment of phacoemulsification and implantation of the innovative intraocular multifocal lens (MFIOL) Oculentis LENTIS Mplus MF30 in patients with bilateral cataracts. Materials and Methods. A single-center prospective observational study was conducted on a total of 20 patients with bilateral cataracts. We evaluated the monocular UCVA and BCVA at 1 day, 7 days, 1 month, 3 months, and 6 months at different distances after phacoemulsification and MFIOL implantation and the binocular UCVA at the same distances. We also assessed the frequency of visual disturbances, overall visual satisfaction, spectacles dependence, and ease of performing different daily activities. Results. The MFIOL Mplus MF30 was able to significantly improve the monocular UCVA and BCVA at all working distances. Overall visual satisfaction was above 9/10 in all postoperative observation intervals. The degree of independence from spectacles at all distances was 100%. The frequency of adverse visual phenomena was minimal. Conclusions. In accordance with the literature, the Oculentis LENTIS Mplus MF30 has proved to be a valid therapeutic alternative for visual rehabilitation after phacoemulsification of the cataract in patients also wishing to treat presbyopia, at the cost of very few visual adverse effects. Trials Registration. This trial is registered with ISRCTN20862627.
Traditional Chinese Sports under China’s Health Strategy
Authors: Yang Fangyan , Zhang Jisheng
Published: August 2022

Chinese traditional sports are diverse and have rich national cultural connotations. However, with the development of China’s Health Strategy, modern sports such as badminton and basketball occupy most of the people’s time. On the contrary, there is much less exercise for traditional Chinese sports. Therefore, this paper aims to study Chinese traditional sports under China’s Health Strategy and explore its cultural soft power. In this study, participants of all ages in different regions were selected for survey research. Combined with the survey results, the soft power index model of Chinese traditional sports culture is designed. The experimental results showed that for Chinese traditional cultural projects, the cultural soft power index of chui wan was the lowest at 0.568, and the highest was 0.982 in the dragon boat culture soft power index. For each evaluation index, the cultural cognition and cultural attractiveness of Chinese traditional sports were high, but the cultural behavioral power was low. This shows that the soft power model of Chinese traditional sports culture based on the healthy China strategic environment can effectively evaluate the development of traditional Chinese sports, which also can provide suggestions for the development and inheritance of traditional Chinese sports.