Miracle-dz/UniFAR-FTUs huggingface dataset:
DL_MONTE: a multipurpose code for Monte Carlo simulation

ABSTRACT DL_MONTE is an open-source, general-purpose software package for performing Monte Carlo (MC) simulations. It includes a wide variety of force fields and MC techniques, and thus is applicable to a broad range of problems in molecular simulation. Here we provide an overview of DL_MONTE, focussing on key features recently added to the package. These include the ability to treat systems confined to a planar pore (i.e. ‘slit’ or ‘slab’ boundary conditions); the lattice-switch Monte Carlo (LSMC) method for evaluating precise free energy differences between competing polymorphs; various commonly used methods for evaluating free energy profiles along transition pathways (including umbrella sampling, Wang–Landau and transition matrix); and a supplementary Python toolkit for simulation management and application of the histogram reweighting analysis method. We provide two ‘real-world’ examples to elucidate the use of these methods in DL_MONTE. In particular, we apply umbrella sampling to calculate the free energy profile associated with the translocation of a lipid through a bilayer. Moreover, we employ LSMC to examine the thermodynamic stability of two plastic crystal phases of water at high pressure. Beyond this, we provide instructions on how to access DL_MONTE and point to additional information valuable to existing and prospective users.
Neurologic Complications of Lyme Disease

ABSTRACT PURPOSE OF REVIEW This article reviews the symptomatology, diagnosis, and treatment of neuroborreliosis. RECENT FINDINGS The most recent guidelines for the diagnosis and treatment of Lyme disease were published in 2020 by the Infectious Diseases Society of America, the American Academy of Neurology, and the American College of Rheumatology. SUMMARY The most common neurologic complications of Lyme disease are cranial neuritis (most often a unilateral or bilateral facial nerve palsy), meningitis, and radiculoneuritis/mononeuropathy multiplex. Testing for Lyme disease begins with an enzyme-linked immunosorbent assay (ELISA). If the ELISA is positive or borderline, Western blots should be performed for both IgM and IgG antibodies. As a general rule, in infectious diseases, an IgM antibody response is followed by an IgG antibody response. A central nervous system infection has either a CSF pleocytosis or pathogen-specific intrathecal antibody production. Lyme meningitis, cranial neuropathy, radiculoneuropathy, or other peripheral nervous system manifestations are treated with oral doxycycline or IV ceftriaxone, cefotaxime, or penicillin G. No additional antibiotic therapy is indicated for patients with posttreatment Lyme disease syndrome or patients with concern for chronic Lyme disease with no evidence of previous or current Lyme infection.
Integrated lane change and ramp metering control at motorway merges

Traffic congestion on motorways is a major societal problem and merging sections are one of the common bottleneck sources on motorways. Merging sections are prone to congestion because of the conflicts between the on-ramp and mainline traffic. These conflicts lead to many negative phenomena such as oscillations, increasing travel times for the road users and a drop in the queue discharge rate after the onset of congestion – more commonly known as capacity drop (Bertini & Malik (2004), Ahn & Cassidy (2007). Ramp metering has been extensively used to control the on-ramp flow entering the mainline and avoid or delay the onset of congestion on the mainline. But ramp metering alone is ineffective when the traffic demand is high.
IMPACT OF DIGITAL TRANSFORMATION IN MEASURING BUSINESS PERFORMANCE OF SMALL & MEDIUM SCALE BUSINESSES IN SRI LANKA

One of the most fundamental social and economic occurrences of our time is digital transformation, which has an impact on business operations. The purpose of this paper is to investigate how digital transformation affects marketing activities in small and medium-sized enterprises (SMEs) in Sri Lanka, as well as to investigate overall changes triggered by digital technology in the marketing concept, its instruments, and activities in SMEs. The primary research question focuses on the current evolution of marketing activities performed by organizations. Analyses and considerations are based on logical inference, examination of empirical study results, a critical literature review, and market observations by the author. Analyses have shown that digital technologies are widely used in marketing in the enterprises studied, despite the fact that these technologies are often classified as traditional tools. IT technologies and digital tools also have an impact on marketing, assisting in the development of customer relationships and increasing the value of each organization.
Complex Predicate Formation via Adjunction to a Head Category: Evidence from Light Verb Constructions in Turkish

The literature on complex predicates which are formed via predicate modification in the sense of Dayal (2011) (further defined as operations of Restrict and Modify in Chung and Ladusaw (2006)) has so far focused primarily on the phenomenon Pseudo Noun Incorporation (PNI). PNI is special in that the object of the verb is interpreted as a predicate, instead of an argument, restricting the event denoted by the verb on the semantic side (Dayal, 2011, cf. Massam, 2001, Van Geenhoven, 1998 among others). In this study, PNI is considered to be a sub-type of complex predication formed via predicate modification, and the main aim here is to explore the syntax of complex predicates by focusing on a new construction in TurkishLight Verb Constructions (LVCs)extending what has been proposed about PNI to that domain, in pursuit of a more general theory. I argue that complex predicates of this type should have a syntactic structure in which one element of the predicate (a head or phrase) adjoins to the other (a head only). The resulting X 0 is interpreted as a complex head on the semantic component, yielding to complex predicate formation, in which the adjoined element restricts/modifies the content of the element that it adjoins to. In LVCs in Turkish, a lexical verb (V1) is followed by a light verb (V2) which either loses its lexical meaning to some extent or becomes fully idiomatic. Light verbs add various aspectual interpretations to the whole complex formed by their combination with the lexical verb. These verbs are as „light‟ in the sense of Grimshaw and Mester (1988) 2 because they are incomplete, requiring a lexical verb to form a complex predicate. When they occur somewhere else other than light verb constructions, they keep their lexical meaning as any other verb does. Three types of LVCs are in the scope of this paper. The first one is such that the suffix -Ip is added on V1 and the inflectional markers (Tense/Aspect/Modality (TAM) and person agreement (PA) markers) appear on V2. I will call this construction „-Ip Type‟. The second one is different from the first one in that V1 gets the suffix -A/-I. I will call this construction „-A Type‟. The third one is „Inflected Type‟, where the two verbs receive the same TAM and PA markers (the name is adopted from Csato, 2003) 3 .
Optimization of Face Detection Based on MTCNN Using Automated Model Compression Method

—The in-depth study of deep learning algorithms across a wide range of applications make it possible to have efficient computer vision tasks today including face detection and alignment such as MTCNN. However, as the neural networks become deeper and complicated, higher computer resources are required to implement it with enough efficiency, making these networks increasingly difficult to deploy in edge AI devices for real-time applications. In this paper, we study reducing the computational and power consumption requirements of MTCNN using an automated network compression method while keeping negligible losses relative to its original state. This optimization approach is effective in minimizing the complexity of convolutional neural networks by introducing sparsity and converting each parameter in the architecture to represent fewer bits integers. The effectiveness of the compression method on MTCNN is demonstrated in NVIDIA Jetson Nano device which shows better performance as compared with the available MTCNN modules from different open-source libraries.
A new brain emotional learning Simulink R (cid:13) toolbox for control systems design (cid:63)

: The brain emotional learning (BEL) control paradigm has been gathering increased interest by the control systems design community. However, the lack of a consistent mathematical formulation and computer based tools are factors that have prevented its more widespread use. In this article both features are tackled by providing a coherent mathematical framework for both the continuous and discrete-time formulations and by presenting a S imulink R (cid:13) computational tool that can be easily used for fast prototyping BEL based control systems
New methodology for establishing the optimal reuse alternative of degraded lands.

Ecological restoration and reuse of degraded lands must contribute to the region's sustainable development. Therefore, in order to determine the post degradation land destination, a number of opportunities and restrictions should be taken into account. For this reason, it is necessary to develop a methodology for establishing the optimal reuse alternative, which should be based on scientific principles, without neglecting economic issues and those related to population requirements. For this purpose the paper is focused on several aspects regarding the restrictions that must be considered in the decision-making process, related to the attraction or dislike of the territory for different ecological restoration options (regional climate, regional topography, ecosystems and land uses, environmental risks, quality indicators of the land etc.). Thus, we developed a methodology for determining the optimal type of land rehabilitation that takes into account a number of factors and indicators and can be applied in all situations, regardless of the form or level of degradation.
Jump-Diffusion Option Valuation and Option-Implied Investor Preferences: A Stochastic Dominance Approach

We investigate the relationship between the discrete-time stochastic dominance option bounds and the continuous time arbitrage-based option pricing models when the underlying asset returns follow a jump-diffusion. Building upon the stochastic dominance approach, we drive multipored index option bounds, violations of which trigger investment strategies that increase the expected utility of any risk-averse trader by introducing a corresponding short (long) option in her portfolio. As trading becomes more frequent, we provide empirical evidence that the bounds converge into a tight limit interval that includes the Merton jump-diffusion price, and compares favorably to the observed bid-ask spreads in option markets. For CRRA investors we also examine the limits of the admissible values of the relative risk aversion coefficient compatible with the boundary risk-neutral distributions extracted from underlying index return data. We show that, unlike the option prices derived from an equilibrium jump diffusion model in both underlying and option markets, the SD bounds can better accommodate reasonable values of the ex-dividend expected excess return. Moreover, the SD-restricted range of admissible RRA values is consistent with the recent macrofinance studies of the equity premium puzzle that show the relative importance of rare disasters in the consumption distribution in explaining the observed equity premium. (JEL G12, G13)
THE PHILIPPINES: THE CHALLENGES OF MORO AND LUMAD POWER-SHARING IN THE BANGSAMORO

Two self-ascribed ethnic groups—Moro and Lumad—are native to Mindanao in the southern Philippines. Both groups share a common history of oppression from Western colonialism, Christian resettlement, and capitalist interests where the former has waged a more organized insurgency against the Philippine government in the late twentieth century. Due to the political superiority of the Moros, the Lumads are often left marginalized in the various peace processes in Mindanao due to their accommodation to the Moro’s call for the creation of anautonomous region under an internal power-sharing agreement. This form of double marginalization against the Lumad promotes a sense of internal colonialism where such arrangements are only left between the Bangsamoro regional government and the Philippine national government, thereby forcing the latter to accommodate to Moro interests. Analyzing the text of the recent peace agreements between the Republic of the Philippines and the Moro Islamic Liberation Front (GRP-MILF), the article attempts to understand the conflict dynamics between Moros and Lumads under power-sharing and power-dividing measures. The article concludes that consociationalismin ethnically divided societies often lead to more ethnic cleavages if done haphazardly to favor certain interests while leaving ethnic minorities at a disadvantage. Keywords: Moro, Lumad, Mindanao, Bangsamoro, consociationalism, identity politics.
New Data Placement Strategy in the HADOOP Framework

Today, the data quantities generated and exchanged between information systems continues to increase. Storing and exploiting such quantities require can’t be done without bigdata systems with mechanisms capable of meeting technological challenges commonly grouped under the four Vs (Volume, Velocity, Variety and Veracity). These technologies include mainly the Distributed File System (DFS). Like Hadoop, which is based on HDFS, the main Big Data systems use a data distributed storage where a subsystem is responsible for subdividing data (data striping) and replicating it on a network of nodes called Grid. In the typical case of Hadoop, a Grid generally consists of many nodes, grouped in multiple Racks. The logic of distributing the stored data through the Grid respects a simple strategy that guarantees the durability of the data and a certain speed of writing. This strategy does not take into consideration neither the technical characteristics of nodes, nor the number of requests on the data, which means a considerable loss in processing capacity of the grid. In this work we proposed a new placement strategy based on exploitation analysis of new information integrated into the HDFS metadata model. A significant 20% improvement in overall processing time was reached through the simulations we conducted on Hadoop. Keywords—Big data; data storage; Hadoop; DFS; HDFS; data striping; chunks; placement strategy; performance optimization
Study of the antiallergic activity of the leaves of Moringa oleifera (moringaceae) in the albino mouse Mus musculus

Allergic diseases are constantly growing, however the efficiency of classical treatments is not total. Thus, new therapeutic tools are considered such as phytotherapy. The objective of this study was to demonstrate the effect of the aqueous extract of Moringa oleifera in mice. The phytochemical study revealed the presence of poly terpenes/sterols, polyphenols, flavonoids, tannins and alkaloids but also the absence of quinones and saponosides. The acute toxicity study at a single dose of 2000 mg/kg body weight (bw) by the oral route revealed that the aqueous extract of Moringa oleifera is not toxic and would have an oral LD50 greater than to 2000 mg/kg bw. The anti-allergic effect of Moringa oleifera leaf Total Aquous Extract (E.T.A.) was evaluated by observing the number of scratching in allergic mice treated orally with two different doses of this extract. A reduction of the number of scratching in mice treated with the extract was observed. This was confirmed by hematological analysis where a considerable increase in the number of immune cells and a decrease in the recruitment of these cells to inflammatory sites were observed. This confirms that the aqueous extract of Moringa oleifera has a dose-dependent antiallergic activity.
THE ROLE OF SITTING POSTURE IN CHRONIC MUSCULOSKELETAL DISORDERS

Sitting is a very common aggravating factor for people with musculoskeletal disorders (MSDs), and alterations in sitting posture are commonly proposed to contribute to the development and aggravation of MSDs. However, the relationship between sitting posture and MSDs is not simple. This paper briefly reviews the relationship between sitting posture and the most common MSD low back pain (LBP) and considers the implications of this for the future of ergonomics in the prevention and management of MSDs.
5G AutoMEC – Boosting edge-to-edge service continuity for CAM in a sliced network

Network function virtualization and edge computing in mobile networks are key enablers in the evolution of recent standards for a 5 Generation (5G) mobile communication system towards a comprehensive 5G ecosystem, which enables the deployment of customized networks and service access for various industry verticals by means of clearly defined and deployed network slices. In particular, the automotive industry can leverage low-latency access to services hosted along the distributed network edge, in support of a large variety of use cases. Network slices typically implement the requested service and network according to a set of defined requirements, as well as performance and latency bounds, while using a defined resources budget. With connected cars following different mobility patterns, the automotive sector represents a pretty agile customer of such network slices. This makes the management of network and edge computing resources a key challenge to tackle in order to balance the resource utilization, and the previously agreed and expected service levels. In this paper, we analyze the benefit of smart mobile edges and the use of machine learning to anticipate resource demand at distributed mobile edges in an automotive scenario. Finally, we experimentally show the feasibility to treat μ-slice resources efficiently by using an OSS-based prototype for the orchestrated edges, which is currently being developed for an automotive trial in Europe.
"CP Based Sequence Mining on the Cloud Using Spark"

Sequential pattern mining (SPM) is a challenging problem concerned with discovering frequent pattern in a given sequence dataset. Due to it's broad range of applications and it's relative complexity, it has been widely studied in the last two decades and a wide variety of efficient approaches have been developed, notably CP-based approaches which combine both great efficiency and flexibility through the addition of constraints. With the advent of Big-data allowing largescale data processing through parallel computation, most specialised approaches evolved further and displayed a qualitative step forward in efficiency. However, CP-based approaches have yet to be adapted to support parallel computations as parallel CP frameworks have yet to be developed. In this paper we thus propose a novel parallel sequential pattern mining approach based on constraint programming modules, and designed to efficiently tackle large-scale data mining problems through parallel computations in a scalable. Document type : Mémoire (Thesis) Référence bibliographique de Vogelaere, Cyril. CP Based Sequence Mining on the Cloud Using Spark. Ecole polytechnique de Louvain, Université catholique de Louvain, 2017. Prom. : Schaus, Pierre. CP Based Sequence Mining on the Cloud Using Spark Dissertation presented by
Low-power thermocatalytic hydrogen sensor based on electrodeposited cauliflower-like nanostructured Pt black

A thermocatalytic hydrogen (H2) gas sensor based on pseudo-porous networks of cauliflower-like nanostructured Pt crystals (Pt black), as the catalytic material, has been fabricated through electrodeposition onto a strip-type suspended microheater (9 μm × 110 μm) for low power sensor operation (8 mW) and fast response speed (1.8 s). The electroplating parameters (solution concentration, current strength, and time) have been tuned for maximum sensitivity and an ionic solution of platinic acid with lead acetate has been used for high adhesion of the catalytic layer. The high catalytic activity of the Pt black, small size of the device, and highly localized electroplating method used allow for sensitive H2 detection: ~0.75% resistance change per %H2 and an estimated 75-ppm lower limit of detection. Additionally, the sensor shows high selectivity against other flammable gases, while consuming much lower power than the commercial catalytic combustion based H2 sensors. The low power consumption attained in this work is expected to help in the constant need for miniaturization of portable devices using catalytic gas sensor for selective detection in industry and for personalized applications.
Construction and Application of Pre-training Model of “Siku Quanshu” Oriented to Digital Humanities

摘要:数字人文研究需要大规模语料库和高性能古文自然语言处理工具支持。 预训练语言模 型已经在英语和现代汉语文本上极大的提升了文本挖掘的精度,目前亟需专门面向古文自动 处理领域的预训练模型。 我们以校验后的高质量《四库全书》全文语料作为训练集,基于 BERT 深度语言模型框架,构建了面向古文智能处理任务的 SikuBERT 和 SikuRoBERTa 预训 练语言模型。 我们设计了面向《左传》语料的古文自动分词、断句标点、词性标注和命名实 体识别 4 个下游任务,分别对我们提出的预训练模型和其他三种用于对比的模型(BERT、 RoBERTa、GuwenBERT)进行微调,验证模型性能。 经过实验,SikuBERT 和 SikuRoBERTa 模型在全部 4 个下游任务中的表现均超越其他预训练模型,表明我们提出的模型具有较强的 古文词法、句法、语境学习能力和泛化能力。 基于表现最优的 SikuRoBERTa 预训练模型, 我们进一步构建了“SIKU-BERT 典籍智能处理平台”,并提供了典籍自动处理、典籍检索和 典籍自动翻译三种在线服务。 该平台可以辅助文献学、古汉语文学、历史学等领域学者在不 具备数据挖掘与深度学习的专业背景下,以简约可视化的方式对典籍文本进行高效率、多维 度、深层次、细粒化的组织处理与分析挖掘。 关键词:数字人文;《四库全书》;预训练模型;深度学习
Analysis and Design of Operational Transconductance Amplifier (OTA) using Cadence tool

: This paper represents the analysis and design of two-stage operational transconductance amplifier (OTA) used in switched-capacitor (SC) circuits. The existing design methods for two-stage OTAs often lead to sub optimal solutions because they decouple inter-related metrics like noise and settling performance. In this approach, the cadence tool is used to analysis the transient response, AC response and phase plot of the OTA and also the settling time has been observed on the simulation. For the optimization routine, there is no need to interface with a circuit simulator because all significant devices parasitic are included in the tool. The simulation results show that a 90-nm prototype amplifier achieves the settling time of 1.5 ns with reduced integrated noise while consuming 2.3 mW from a 1.1V power supply with phase plot for 174 degree.
High Performance Feedback Linearization Control of Induction Motor

In induction motor control, power efficiency is an important factor to be considered. We attempt to achieve both high dynamic performance and maximum power. In this paper a feedback linearization controller is presented for Induction Motor drive. The controller is designed based on the adaptive input-output feedback linearization control technique. The effects of variations in mechanical parameter values on the linearized system are derived and discussed. The subject of this paper is to ascertain various controller’s algorithms’ advantages and disadvantages and give recommendations for it’s use under certain conditions and in distinct applications. The drive will be studied as fairly as possible by discussing it’s parameter sensitivities, dynamic responses, and steady-state errors. Computer simulation results obtained, confirm the effectiveness and validity of the proposed control approach.