Miracle-dz/UniFAR-FTUs huggingface dataset:
ALIGNING MARKETING AND MANUFACTURING STRATEGIES WITH THE MARKET

In strategic marketing decisions substantial emphasis is placed on market segmentation and product/service differentiation. This follows from separate, intensive analyses of customers and competitors. Based on these analyses, the resultant segmentation and differentiation schema, and an intensive review of the firm's own strengths, weaknesses, opportunities and threats, the firm makes one of its most important and critical decisions: which customers to serve and which products to emphasize, referred to as positioning. On the other side of the same corporate coin, manufacturing makes decisions on process and infrastructure investments based upon the technologies required, and its perception of what it needs to do well in order to fulfil its role. In the same way as with marketing decisions, the firm now makes another of its most critical decisions by committing itself to major investments in manufacturing that are characterized by high value and long time scales to change. On the one hand, these positionin.
The effect of sheet resistance modifications underneath the contact on the extraction of the contact resistivity: application to the cross Kelvin resistor

The influence of sheet-resistance modifications underneath the contact on the extraction of the contact resistivity is investigated. A generalized scaling theory has been applied to the modeling of the cross Kelvin resistor. It is shown that the errors associated with the contact sheet resistance modification could become appreciable in low-resistance metallizations of interest in VLSI. >
A Robotic Milling System Based on 3D Point Cloud

Industrial robots have advantages in the processing of large-scale components in the aerospace industry. Compared to CNC machine tools, robot arms are cheaper and easier to deploy. However, due to the poor consistency of incoming materials, large-scale and lightweight components make it difficult to automate robotic machining. In addition, the stiffness of the tandem structure is quite low. Therefore, the stability of the milling process is always a concern. In this paper, the robotic milling research is carried out for the welding pre-processing technology of large-scale components. In order to realize the automatic production of low-conformity parts, the on-site measurement–planning–processing method is adopted with the laser profiler. On the one hand, the laser profiler hand–eye calibration method is optimized to improve the measurement accuracy. On the other hand, the stiffness of the robot’s processing posture is optimized, combined with the angle of the fixture turntable. Finally, the experiment shows the feasibility of the on-site measurement–planning–processing method and verifies the correctness of the stiffness model.
Ecological interactions mediate projected loss of kelp biomass under climate change

Climate change has precipitated loss of kelp in temperate regions globally, with further losses projected in response to ocean warming. Projected climate‐driven changes to kelp are commonly derived from responses to sea surface temperature and neglect the effects of important ecological interactions, such as herbivory. Here, we use a stacked species distribution model to project impacts of future climate scenarios on kelp distribution and biomass incorporating the effects of key ecological interactions.
Autophagy-related protein Atg11 preserves asymmetric inheritance of spindle microtubule-organizing centers

Asymmetric spindle pole body (SPB) inheritance requires a cascade of events that involve kinases, phosphatases and structural scaffold proteins including molecular motors and microtubule-associated proteins present in the nucleus and/or the cytoplasm. Higher levels of an SPB component Spc72 and the spindle positioning factor Kar9 at the old SPB, which migrates to the daughter cell, ensure asymmetric SPB inheritance. Timely SPB duplication followed by its asymmetric inheritance is a key to correct spindle alignment leading to high-fidelity chromosome segregation. By combining in silico analysis of known protein-protein interactions of autophagy (Atg)-related proteins with those that constitute the chromosome segregation machinery, and growth dynamics of 35 atg mutants in the presence of a microtubule poison, we identified Atg11 as a potential regulator of chromosome transmission. Cells lacking Atg11 did not show any kinetochore defects but displayed a high rate of chromosome loss and delayed anaphase onset. Atg11 positively interacted with Kar9 and Kip2 and negatively with Dyn1 and Kar3 in mediating proper chromosome segregation suggesting a role of Atg11 in spindle positioning. Indeed, atg11∆ cells displayed an inverted SPB inheritance. We further show that Atg11 promotes asymmetric localization of Spc72 and Kar9 on the old SPB. Atg11 physically interacted with Spc72 and transiently localized close to the old SPB during metaphase-to-anaphase progression. Taken together, our study uncovers an autophagy-independent role of Atg11 in spindle alignment and emphasizes the importance of unbiased screens to identify factors mediating the complex and intricate crosstalk between processes fundamental to genomic integrity.Dysregulation in spindle alignment during cell division causes decreased lifespan and contributes to diseased states related to aneuploidy such as cancer. The alignment of the mitotic spindle along the mother-bud axis in the budding yeast relies on the differential distribution of proteins between existing old and freshly formed new spindle pole bodies (SPBs). Non-random distribution of Spc72 and Kar9 facilitates the asymmetric inheritance of SPBs, vital for proper spindle elongation and alignment. Here, we identified a non-canonical role of an autophagy-related protein Atg11 in the Kar9-mediated spindle positioning and faithful chromosome segregation. Loss of Atg11 leads to randomized Spc72 distribution. Atg11, like other autophagy proteins, is evolutionarily conserved. Thus, this study reiterates the importance of crosstalk among major biological processes.
Sparse Lp-Norm Based ICP for 3D Registration

In order to uncover truths to serve justice, case-related data collected from a digital investigation requires substantial resources to analyze, especially in time-critical situations. At present, however, digital forensics has not evolved to meet this ever-increasing demand. Digital forensic triage is a promising solution, as it is designed to maximize the use of resources according to a system of priorities, and hence the efficiency and effectiveness of forensic examinations can be increased. Nevertheless, the lack of concrete methods limits efforts to implement triage. This paper presents a practical approach that is designed to build a prioritizing solution. In this work a newprocess model is derived based on the presented approach, and it is particularly suited to scenarios where forensic examiners do not have enough time and resources to conduct a full examination and analysis. An example is described to demonstrate how this approach can be used to meet the requirements of network forensic investigations.
Voltage regulation coordination of distributed generation system in distribution system

This paper proposes a new voltage regulation coordination method of DGS (distributed generation system) for proper voltage regulation in distribution system using LCT (load-tap changing transformer) and LDC (line drop compensator). The method is that DGS coordinates the distribution system voltage regulation by controlling its reactive power output according to its real power output. The proposed method is applied to the power distribution system model, and its effectiveness is verified through simulation results.
Exercise Training for Multiple Sclerosis: A Narrative Review of History, Benefits, Safety, Guidelines, and Promotion

Background: There have been significant advances in the medical treatment and management of multiple sclerosis pathogenesis, relapse and disease progression over the past 30 years. There have been advancements in the symptomatic treatment of multiple sclerosis, including management of secondary multiple sclerosis expressions such as walking, cognitive dysfunction, fatigue and depression. Scientific evidence and expert opinion suggest that exercise may be the single most effective non-pharmacological symptomatic treatment for multiple sclerosis. This article presents the historical context of exercise training within the multidisciplinary management of multiple sclerosis. We guide neurologists and healthcare providers on the recommended prescription of exercise and practical, theoretical methods to overcome barriers to exercise. Method: We undertook a critical search of the historical and current literature regarding exercise and multiple sclerosis from the viewpoint of exercise promotion by neurologists and the multidisciplinary care team. Results: We highlight the ever-strengthening body of research indicating that exercise is safe and effective for improving symptoms of multiple sclerosis. Further, exercise training may be necessary for reducing disease progression. Conclusion: We seek to encourage neurologists and specialists in multidisciplinary healthcare teams to prescribe and promote exercise at diagnosis and across all stages of the disease trajectory using prescriptive guidelines as part of comprehensive MS care. Available tools include clinical education to dispel any historical myths related to exercise in multiple sclerosis, clinical exercise guidelines and behaviour change theory to overcome patients barriers to exercise.
Counter-terrorism threat prediction architecture

This paper will evaluate the feasibility of constructing a system to support intelligence analysts engaged in counter-terrorism. It will discuss the use of emerging techniques to evaluate a large-scale threat data repository (or Infosphere) and comparing analyst developed models to identify and discover potential threat-related activity with a uncertainty metric used to evaluate the threat. This system will also employ the use of psychological (or intent) modeling to incorporate combatant (i.e. terrorist) beliefs and intent. The paper will explore the feasibility of constructing a hetero-hierarchical (a hierarchy of more than one kind or type characterized by loose connection/feedback among elements of the hierarchy) agent based framework or "family of agents" to support "evidence retrieval" defined as combing, or searching the threat data repository and returning information with an uncertainty metric. The counter-terrorism threat prediction architecture will be guided by a series of models, constructed to represent threat operational objectives, potential targets, or terrorist objectives. The approach would compare model representations against information retrieved by the agent family to isolate or identify patterns that match within reasonable measures of proximity. The central areas of discussion will be the construction of an agent framework to search the available threat related information repository, evaluation of results against models that will represent the cultural foundations, mindset, sociology and emotional drive of typical threat combatants (i.e. the mind and objectives of a terrorist), and the development of evaluation techniques to compare result sets with the models representing threat behavior and threat targets. The applicability of concepts surrounding Modeling Field Theory (MFT) will be discussed as the basis of this research into development of proximity measures between the models and result sets and to provide feedback in support of model adaptation (learning). The increasingly complex demands facing analysts evaluating activity threatening to the security of the United States make the family of agent-based data collection (fusion) a promising area. This paper will discuss a system to support the collection and evaluation of potential threat activity as well as an approach fro presentation of the information.
Feature selection for defect classification in machine condition monitoring

A M As the sensitivily of various parameters to a defect condition of a machine differs, it i s imperative to devise a feature selection scheme that selects the best parameters to maximize the accuracy of the &feet classification scheme A feature selection scheme based on principal component analysis (PCA) is proposed in this paper. A methodology was developed for bearing defect classificatwn using. neural newrks. The scheme has shown to provide more accurate defect classifcation with less parameter inputs than using all parameters initially considered relevant
ORGANISATIONAL CULTURE CHANGE AT KENYA POWER AND LIGHTING COMPANY LIMITED

ix CHAPTER ONE: INTRODUCTION . 1 1.1 Background of the Study . 1 1.1.1 Organizational Culture . 2 1.1.2 Change Management . 3 1.1.3 Energy Sector in Kenya . 4 1.1.4 Kenya Power and Lighting Company Limited . 5 1.2 Research Problem . 7 1.3 Research Objective . 9 1.4 Value of the Study . 9 CHAPTER TWO: LITERATURE REVIEW . 10 2.
DEEP NEURAL NETWORKS FOR IMAGE SUPER-RESOLUTION IN OPTICAL MICROSCOPY BY USING MODIFIED HYBRID TASK CASCADE U-NET

|Due to the optical diﬀraction limit, the resolution of a wide-(cid:12)eld (WF) microscope cannot easily go below a few hundred nanometers. Super-resolution microscopy has the disadvantages of high cost, complex optical equipment, and high experimental environment requirements. Deep-learning-based super-resolution (DLSR) has the advantages of simple operation and low cost, and has attracted much attention recently. Here we propose a novel DLSR model named Modi(cid:12)ed Hybrid Task Cascade U-Net (MHTCUN) for image super-resolution in optical microscopy using the public biological image dataset BioSR. The MHTCUN has three stages, and we introduce a novel module named Feature Re(cid:12)nement Module (FRM) to extract deeper features in each stage. In each FRM, a U-Net is introduced to re(cid:12)ne the features, and the Fourier Channel Attention Block (FCAB) is introduced in the U-Net to learn the high-level representation of the high-frequency information of diﬀerent feature maps. Compared with six state-of-the-art DLSR models used for single-image super-resolution (SISR), our MHTCUN achieves the highest signal-to-noise ratio (PSNR) of 26.87 and structural similarity (SSIM) of 0.746, demonstrating that our MHTCUN has achieved the state-of-the-art in DLSR. Compared with the DLSR model DFCAN used for image super-resolution in optical microscopy specially, MHTCUN has a signi(cid:12)cant improvement in PSNR and a slight improvement in SSIM on BioSR. Finally, we (cid:12)ne-tune the trained MHTCUN on the other biological images. MHTCUN also shows good performance on denoising, contrast enhancement, and resolution enhancement.
On the Use of MOS Varactors in RF VCO's

This paper presents two 1.8-GHz CMOS voltage-controlled oscillators (VCO's), tuned by an inversion-mode MOS varactor and an accumulation-mode MOS varactor, respectively. Both VCO-s show a lower power consumption and a lower phase noise than a reference VCO tuned by a more commonly used diode varactor. The best overall performance is displayed by the accumulation- mode MOS varactor VCO. The VCO's were implemented in a standard O.6-? m CMOS process.
Two complementary approaches to estimate downwash lag effects from flight data

ALIDATION of the wind-tunnel and analytical estimates of the aerodynamic derivatives with estimates from flight test data is an important application of the system identification methodology. Reliable and accurate estimates of a large number of aerodynamic derivatives are obtained from flight data using the maximum likelihood method, although, routinely, explicit accounting for certain unsteady aerodynamic effects such as downwash and sidewash interferences pose difficulties. Recent advances in both parameter estimation methods and in flight test techniques have provided a new impetus for modeling and identification of such unsteady interference effects in aircraft dynamics.1'3 This Note addresses in some depth the problem of accounting for downwash lag effects in aircraft parameter estimation from flight data. One possibility of including such an effect is to proceed from the fundamental and to model the forces acting on the wing and tail plane separately. In such a case it becomes possible to estimate explicitly the downwash angle and also to include the lag effect. It leads, however, to a model that is nonlinear in parameters and necessarily requires an estimation program capable of handling nonlinear model postulates. The other approach is a simplification based on linearization. It leads to the first-order approximation of aerodynamic derivatives with respect to translational acceleration. The derivatives due to the body-fixed translational acceleration in the vertical direction are equivalent in the stability axis to those with respect to the rate of change of angle of attack. The second approach was first investigated in Ref. 1 to estimate from flight data the pitching moment derivatives with respect to pitch rate and rate of change of angle of attack of a highly maneuver able aircraft with large roll angle capabilities. A parameter estimation program capable of handling linear as well as nonlinear system models is used here to compare the two approaches of accounting for the downwash. Further, an attempt is made to investigate the possibility of using the linearized approach to estimate separately the two pitch damping derivatives from flight tests with a larger aircraft having limited roll angle capabilities.
Intra-family communication needs; how can awareness systems provide support?

This paper presents the concept of ambient awareness that pertains to using ambient intelligence technologies for the purposes of sustaining awareness between individuals or groups of people, over sustained periods of time. The first explorations of this concept are conducted within the context of supporting awareness for busy parents having young children. We sketch the requirements drawn from an interview study, involving 20 interviews with working parents and we identify unmet communication needs that this type of technology may support
Pengaruh Sistem Pengendalian Manajemen Terhadap Kinerja Strategic Supply Relationship; Dengan Kerjasama Sebagai Variabel Intervening

The important of management control system (MCS) has been documented in MCS literature. In addition, performance measurement system and socialization are some of aspects of MCS that could improve the company performance. Recent development in MCS have heightened the need of sustainable strategic supply relationships (SRRs). However, far too little attention has been paid to strategic supply relationship performance, especially from supplier’s perspective. Therefore, the objective of this study is to determine whether the performance measurement system (PMS), socialization are significantly associated with the performance of strategic supply relationship. Further, the analysis extend to whether the PMS and Socialization influence the performance SSRs through corporations (or corporation as intervening variable). The study use 101 companies as respondents and structural equation model (SEM) as data analysis. The result reveal that performance measurement system and socialization have a positive significantly relationship with the corporation. Further analysis show that PMS is also positively significant associated with the SSRs performance and socialization, however, do not have a significant relationship with the performance SSRs. Contrary to expectation, corporation also do not have a significant relationship with the performance. The most striking result to emerge from the data is that there is no role of corporation as intervening variable in this study. Theses findings has an important implication for developing the SSRs performance of PT. Semen Padang. Further, these combination of findings provide some support for conceptual premises that belong to the contivency theory which explain that the company performance contigent upon the internal and external factors.
Halogenated Ti3C2 MXene as a High Capacity Electrode Material for Li-ion Batteries

: MXenes have been widely studied for their excellent specific surface area, high conductivity and compo-sition tunability, which have been used as a highly efficient electrode material for lithium-ion batteries (LIBs). How-ever, limited storage capacity and severe lattice expansion caused by Li-ions diffusion restrict the application of MXenes as electrode materials. Here, Ti 3 C 2 MXenes with surface halogenation (fluorination, chlorination and bromination) as representative MXene materials were designed. Effects of surface functionalization on the atomic structures, electronic properties, mechanical properties, and electrochemical performance of Ti 3 C 2 T 2 (T = F, Cl and Br) anode in LIBs were investigated using first-principles calculations based on density functional theory with van der Waals correction. The results reveal that Ti 3 C 2 T 2 MXenes exhibit metallic conductivity with improved structural stability and mechanical strength. Compared with Ti 3 C 2 F 2 and Ti 3 C 2 Br 2 , Ti 3 C 2 Cl 2 exhibits the large elastic modulus (321.70 and 329.43 N/m along with x and y directions, respectively), low diffusion barrier (0.275 eV), high open circuit voltage (0.54 eV), and storage capacity (674.21 mA·h/g) with stoichiometric ratio at Ti 3 C 2 Cl 2 Li 6 , which renders the enhanced rate performance and endures the repeated lattice expansion and contraction during charge/discharge process. Moreover, surface chlorination yields expanded interlayer spacing, which can improve Li-ion accessibility and fast charge–discharge rate in Ti 3 C 2 Cl 2 . The research demonstrates that Cl – terminated Ti 3 C 2 is a promising anode material, and provides effective and reversible routes to engineering other MXenes as anode materials for LIBs.
New DC-DC converters with an energy storage reactor

New DC-DC power converters with an energy storage reactor are presented. In the conventional converter circuits of an energy storage reactor, there is an extraordinary increase of the output voltage due to the excess magnetic energy, when the reactor current becomes discontinuous for the light-load. This phenomenon can be removed by making use of a dummy load or a reactor of sufficiently large inductance. However, the use of the dummy load makes the efficiency poorer and the size as well as the weight becomes larger if the inductance of the reactor is increased. In the converter circuits presented, the excess magnetic energy, which is stored in the reactor and undissipated in the load circuit, can be recovered to the input power source through the additional transistor and diode. With these converter circuits, the dummy load can be removed for any load condition and further the inductance of the reactor can be made smaller.
Performance analysis of salient-pole self-excited reluctance generators using a simplified model

A simple, direct mathematical model is developed for steady-state analysis of salient-pole, self-excited synchronous reluctance generators. The model does not require either the power consumed by the load or the ratio of the load to excitation current to be estimated which are prerequisite assumptions of previous analysis techniques. The model is verified by experiment which includes assessment of critical speed, excitation capacitance, no-load terminal voltage and voltage regulation on load. The experiments are performed using a prototype synchronous reluctance generator. The analysis technique is then used to investigate the effect that saliency, stator resistance and power factor have on the performance of the self-excited system.