Miracle-dz/UniFAR-FTUs huggingface dataset:
Attribution Modelling in Marketing: Literature Review and Research Agenda

The dilemma of allocation of marketing budget to multi-channels is faced by the practitioners and has remained an interesting area of research for the academia. This paper investigates and synthesizes different models and techniques used for allocation of marketing budget for three decades i.e. 1990-2019. Authors have used the PRISMA technique to create a corpus of relevant research articles. The classification of literature is done based on three broad categories i.e. constructs studied, usage of marketing channels, and models of attribution modelling. The analysis revealed that 71% of research articles were published in A* and A category of ABDC ranked journals. Around 67% of the articles on attribution modelling were published during 2014-2019 making it one of the thrust areas for research in marketing discipline. Based on the synthesis of previous literature, the prominent models used by the researchers to solve the attribution problem were Markov chain, Probit model, Linear models among others. Lastly, authors provided a conceptual framework for the ensemble model combining the properties of the Markov chain model and Shapley value to make a robust model
Classifying the Photophysical Dynamics of Single- and Multiple-Chromophoric Molecules by Single Molecule Spectroscopy

The single molecule fluorescence spectroscopy of various isolated single-chromophoric dye molecules and multiple-chromophoric conjugated polymer molecules has been investigated. For each system the transient fluorescence “intensity”, ICW(t) (i.e., detected photons/dwell time), has been recorded with continuous wave (CW) irradiation. ICW(t) has been analyzed to yield an occurrence histogram for the different “intensities”, H(I), and an intensity time-autocorrelation function CI(t). The histograms H(I) for the various examples show highly diverse behavior with one, two, or even three peaks as well as “flat regions”. The different features in the histograms are shown to arise from distinct photophysical processes. From the study of model systems, characteristic features in the intensity histograms and autocorrelation functions are shown to result from photon shot noise, “blinking” due to triplet bottlenecks, spectral diffusion due to environmental fluctuations, and interchromophoric energy transfer. Classifi.
Self-consistent mean field theory of the microphases of diblock copolymers

Using self-consistent mean field theory, the phase behavior of diblock copolymers was examinedfrom the weak to the strong segregation regimes, considering spherical, cylindrical, and lamellar microphases. It was shown that the phase diagram depends on three quantities: χrc where rc is an effective degree of polymerization, the relative volume fractions of each block, and e= (ρ 0B b B 2 )/(ρ 0A b A 2 ) where ρ 0P and b p are the pure component density and Kuhn length for each block. The phase diagram, domain sizes and density profiles were calculated for e= 1.
An investigation of extremity injuries in school-aged children presenting to the emergency department

Aim: It was aimed that various preventive measures should be taken with the demographic characteristics, trauma etiology, injury sites and radiological imaging results of school-age pediatric patients admitted to the emergency department after isolated extremity trauma. Material and Methods: In our two-center study, 748 patients with isolated limb injuries aged 6-17 years were prospectively evaluated. Their gender, age, causes of trauma, requested radiological imaging in patients classified according to injury sites, treatments, requested consultations, hospitalization and discharge rates were examined. Results: The mean age was 12.2 ± 3.2 years. The most common cause of injury (52.8%) was fall while playing. Fall while playing (FWP) and extremity injuries occurring during sport were more in males than females (p = 0.020). When injury sites were compared according to trauma etiologies, injuries were observed mostly in the left upper extremity in FWPs and mostly in the right upper extremity in school accidents (p = 0.009). An orthopedic consultation request was high in patients who underwent splinting and surgical treatment (p = 0.000). While fracture was detected in 136 (18.1%) patients included in the study, splint or Velpeau bandage treatments were applied to 314 (41.9%) patients. Conclusion: In school-aged child injuries, the most common cause was observed to be "fall," which is a preventable cause. Protective measures that will be taken for the safety of children at home, playgrounds, and schools can reduce these injuries.
Improved Metric Learning With the CNN for Very-High-Resolution Remote Sensing Image Classification

The number of labeled samples has a great impact on the classification results of a very-high-resolution (VHR) remote sensing image. However, the acquisition of available labeled samples is difficult and time consuming. Faced with the limited labeled samples on a high-resolution remote sensing image, a semisupervised method becomes an effective way. In semisupervised learning, an accurate similarity prediction between unlabeled and labeled samples is very important. However, a reliable similarity prediction between high-dimensional features is difficult. For more reliable similarity prediction for the high-dimensional feature, a novel semisupervised classification framework via improved metric learning with a convolutional neural network is proposed. In the proposed method, a novel trainable metric learning network is designed to accurately evaluate the similarity between high-dimensional features. The vector distance parameter solving problem is transformed into a neural network design problem, which can automatically calculate parameters by the back-propagation algorithm. Finally, the pixel constraint mechanism is introduced to select the unlabeled samples. Experimental results conducted on three VHR remote sensing images, including Aerial, Xi’an, and Pavia University, and the results present that the proposed method performs better than the compared state-of-the-art methods.
A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology management is a crucial requirement, and in particular in massive scale deployments. Traditionally, clustering has been recognized as a common approach for topology management in ad-hoc networks, e.g., in Wireless Sensor Networks (WSNs). Topology management in WSNs and ad-hoc IoT networks has many design commonalities as both need to transfer data to the destination hop by hop. Thus, WSN clustering techniques can presumably be applied for topology management in ad-hoc IoT networks. This requires a comprehensive study on WSN clustering techniques and investigating their applicability to ad-hoc IoT networks. In this article, we conduct a survey of this field based on the objectives for clustering, such as reducing energy consumption and load balancing, as well as the network properties relevant for efficient clustering in IoT, such as network heterogeneity and mobility. Beyond that, we investigate the advantages and challenges of clustering when IoT is integrated with modern computing and communication technologies such as Blockchain, Fog/Edge computing, and 5G. This survey provides useful insights into research on IoT clustering, allows broader understanding of its design challenges for IoT networks, and sheds light on its future applications in modern technologies integrated with IoT.
Leaching and plant offtake of N in field pea/cereal cropping sequences with incorporation of 15N‐labelled pea harvest residues

Abstract. Field peas (Pisum sativum L.) were grown in sequence with winter wheat (Triticum aestivum L.) or spring barley (Hordeum vulgare L.) in large outdoor lysimeters. The pea crop was harvested either in a green immature state or at physiological maturity and residues returned to the lysimeters after pea harvest. After harvest of the pea crop in 1993, pea crop residues (pods and straw) were replaced with corresponding amounts of 15N‐labelled pea residues grown in an adjacent field plot. Reference lysimeters grew sequences of cereals (spring barley/spring barley and spring barley/winter wheat) with the straw removed. Leaching and crop offtake of 15N and total N were measured for the following two years. These treatments were tested on two soils: a coarse sand and a sandy loam. Nitrate concentrations were greatest in percolate from lysimeters with immature peas. Peas harvested at maturity also raised the nitrate concentrations above those recorded for continuous cereal growing. The cumulative nitrate loss was 9–12 g NO3‐N m–2 after immature peas and 5–7 g NO3‐N m–2 after mature peas. Autumn sown winter wheat did not significantly reduce leaching losses after field peas compared with spring sown barley. 15N derived from above‐ground pea residues accounted for 18–25% of the total nitrate leaching losses after immature peas and 12–17% after mature peas. When compared with leaching losses from the cereals, the extra leaching loss of N from roots and rhizodeposits of mature peas were estimated to be similar to losses of 15N from the above‐ground pea residues. Only winter wheat yield on the coarse sand was increased by a previous crop of peas compared to wheat following barley. Differences between barley grown after peas and after barley were not statistically significant. 15N lost by leaching in the first winter after incorporation accounted for 11–19% of 15N applied in immature pea residues and 10–15% of 15N in mature residues. Another 2–5% were lost in the second winter. The 15N recovery in the two crops succeeding the peas was 3–6% in the first crop and 1–3% in the second crop. The winter wheat did not significantly improve the utilization of 15N from the pea residues compared with spring barley.
Solubility Advantage of Pharmaceutical Cocrystals

Pharmaceutical cocrystals can improve solubility, dissolution, and bioavailability of poorly water soluble drugs. However, true cocrystal solubility is not readily measured for highly soluble cocrystals because they can transform to the most stable drug form in solution. The objectives of this study are to develop a method to estimate the cocrystal solubility in pure solvent and establish the influence of constituent drug and ligand (i.e., coformer) properties. Cocrystal solubility and solubility product were derived from transition concentration measurements where a solution is in equilibrium with solid drug and cocrystal. Transition concentrations and solubilities are reported for carbamazepine cocrystals in water, ethanol, isopropanol, and ethyl acetate. The aqueous solubility for seven carbamazepine cocrystals was estimated to be 2−152 times greater than the solubility of the stable carbamazepine dihydrate form. Cocrystal solubility is shown to be directly proportional to the solubility of constituent.
Gradient-Based Optimization of PCFM Radar Waveforms

While a number of signal structures have been proposed for radar, frequency modulation (FM) remains the most common in practice because it is well-suited to high-power transmitters, which tend to introduce significant distortion to other waveform classes. That said, various forms of coding provide useful parameterizations for which a variety of optimization methods can be readily applied to accomplish different operational goals. To that end, the polyphase-coded FM (PCFM) implementation was previously devised as a means to bridge this gap between optimizable parameters and physically realizable waveforms. However, the original method employed to optimize PCFM waveforms involved a piecewise greedy search that, while relatively effective, was rather slow and cumbersome. Here, the continuous nature of this framework is leveraged to formulate a gradient-based optimization approach that updates all parameters simultaneously and can be efficiently performed using fast Fourier transforms, thus facilitating a general design methodology for practical waveforms that is directly extensible to myriad waveform-diverse arrangements. Results include a large number of optimization assessments to discern performance trends in aggregate and detailed analysis of specific cases, as well as both loopback and free-space experimental measurements to demonstrate practical efficacy.
EOS architectural evolution and strategic development directions

EOS [1] is the main storage system at CERN providing hundreds of PB of capacity to both physics experiments and also regular users of the CERN infrastructure. Since its first deployment in 2010, EOS has evolved and adapted to the challenges posed by ever-increasing requirements for storage capacity, user-friendly POSIX-like interactive experience and new paradigms like collaborative applications along with sync and share capabilities. Overcoming these challenges at various levels of the software stack meant coming up with a new architecture for the namespace subsystem, completely redesigning the EOS FUSE module and adapting the rest of the components like draining, LRU engine, file system consistency check and others, to ensure a stable and predictable performance. In this paper we detail the issues that triggered all these changes along with the software design choices that we made. In the last part of the paper, we move our focus to the areas that need immediate improvements in order to ensure a seamless experience for the end-user along with increased over-all availability of the service. Some of these changes have far-reaching effects and are aimed at simplifying both the deployment model but more importantly the operational load when dealing with (non/)transient errors in a system managing thousands of disks.
Challenges and Promises of Electrochemical Detection and Sensing

The field of electrochemical detection and sensing is briefly surveyed. Some general problems are pointed out, e.g., the limited reproducibility of the sensor surface, difficulties with the long-term stability of sensors, or slow response of many electrochemical devices. On the other hand, promises and opportunities for the future involve further sensor miniaturization, combination of sensing and detection with chemometric techniques and/or with other measuring techniques, potentialities of in vivo measurements in biological objects, or mass production of simple and low cost single-use sensors.
Binary Linear Codes With Optimal Scaling: Polar Codes With Large Kernels

We prove that, for the binary erasure channel (BEC), the polar-coding paradigm gives rise to codes that not only approach the Shannon limit but do so under the <italic>best possible scaling of their block length</italic> as a function of the gap to capacity. This result exhibits the first known family of binary codes that attain both optimal scaling and quasi-linear complexity of encoding and decoding. Our proof is based on the construction and analysis of binary polar codes <italic>with large kernels</italic>. When communicating reliably at rates within <inline-formula> <tex-math notation="LaTeX">$\varepsilon > 0$ </tex-math></inline-formula> of capacity, the code length <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> often scales as <inline-formula> <tex-math notation="LaTeX">$O(1/\varepsilon ^{\mu })$ </tex-math></inline-formula>, where the constant <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> is called the <italic>scaling exponent</italic>. It is known that the optimal scaling exponent is <inline-formula> <tex-math notation="LaTeX">$\mu =2$ </tex-math></inline-formula>, and it is achieved by random linear codes. The scaling exponent of conventional polar codes (based on the <inline-formula> <tex-math notation="LaTeX">$2\times 2$ </tex-math></inline-formula> kernel) on the BEC is <inline-formula> <tex-math notation="LaTeX">$\mu =3.63$ </tex-math></inline-formula>. This falls far short of the optimal scaling guaranteed by random codes. Our main contribution is a rigorous proof of the following result: for the BEC, there exist <inline-formula> <tex-math notation="LaTeX">$\ell \times \ell $ </tex-math></inline-formula> binary kernels, such that polar codes constructed from these kernels achieve scaling exponent <inline-formula> <tex-math notation="LaTeX">$\mu (\ell)$ </tex-math></inline-formula> that tends to the optimal value of 2 as <inline-formula> <tex-math notation="LaTeX">$\ell $ </tex-math></inline-formula> grows. We furthermore characterize precisely how large <inline-formula> <tex-math notation="LaTeX">$\ell $ </tex-math></inline-formula> needs to be as a function of the gap between <inline-formula> <tex-math notation="LaTeX">$\mu (\ell)$ </tex-math></inline-formula> and 2. The resulting binary codes maintain the recursive structure of conventional polar codes, and thereby achieve construction complexity <inline-formula> <tex-math notation="LaTeX">$O(n)$ </tex-math></inline-formula> and encoding/decoding complexity <inline-formula> <tex-math notation="LaTeX">$O(n\log n)$ </tex-math></inline-formula>.
Oak competitive status in 27-year-old group openings in a West Gulf Coastal Plain pine-hardwood forest

Due to their high ecological and economic value, oaks (Quercus spp.) are a desirable species group for mixedwood management. However, little information exists on oak competitiveness at the local, neighborhood scale in harvest gaps beyond the first few growing seasons. The objective of this research is to determine if oak competitive status is related to neighborhood composition and gap size. A total of 156 oak stems at least 3.5 inches in diameter at breast height and their respective neighborhoods were sampled in nine experimental harvest gaps (ranging in size from 0.25 to 1.0 acre) on the Kisatchie National Forest. Using neighborhood species importance values, a cluster analysis identified five neighborhood types: pine (Pinus spp.), pine-sweetgum (Liquidambar styraciflua), pine-oak, mixed hardwood-pine, and oak. No significant effects of neighborhood type or gap size were detected for subject tree heights or competition index; however, gap size was a significant factor in explaining red oak (section Lobatae) live crown ratio, and neighborhood type was a significant factor in predicting live crown ratio of all oaks. Red oaks in smaller gaps had significantly higher live crown ratios when compared to those in medium or large gaps. Oaks in pine neighborhoods had significantly lower live crown ratios when compared to neighborhoods with a greater hardwood component. These results suggest that managers should consider implementing timber stand improvement earlier in gap development to release oaks from pine and other shade-intolerant competition if earlier canopy recruitment of oak is desired. Alternative research approaches may be required to fully evaluate oak competitive status in gap cohorts initiated by group selection, such as stem analysis of oak subjects and neighbors and including oaks of all size classes.
Impact Angle Control Guidance of Glide-Capable Munition Using a Vector Field Approach

A vector field-based guidance law is proposed for the speed and impact angle control of an unpowered, glide-capable air-to-ground munition. An artificial 3-D space is designed for the glider vehicle to satisfy the terminal constraints. The glider vehicle is guided to the target position by the proposed vector field-based guidance law while satisfying the desired impact angle and final speed constraints. In the numerical simulations, various wind conditions are considered to demonstrate the performance of the proposed guidance law.
A Kerr magneto‐optical microscope using polaroid polarizers

SYNOPSIS The Kerr-effect microscope is of great utility in the static and dynamic investigation of magnetic domain patterns in thin films used for computer storage. An account is presented of the theoretical considerations which decide the optimum instrumental configuration for maximum contrast and this leads to two microscope designs: one using a single lens, and the other, two lenses. The type of domain shown by these microscopes is illustrated.
Model Organic Surfaces to Probe Marine Bacterial Adhesion Kinetics by Surface Plasmon Resonance

Understanding how bacteria adhere to a surface is a critical step in the development of novel materials and coatings to prevent bacteria forming biofilms. Here, surface plasmon resonance (SPR) spectroscopy, in combination with self‐assembled monolayers (SAMs) that have different backbone structures and/or functional groups, is used for the first time to study the initial stages of bacterial adhesion to surfaces (i.e., initial interaction of cells with a surface, a process governed by van der Waals, electrostatic, and hydrophobic interactions). The work highlights SPR spectroscopy as a powerful and unique approach to probe bacterial adhesion in real time. SPR spectral data reveal different kinetics of adhesion for the interaction of two marine bacterial species (Marinobacter hydrocarbonoclasticus and Cobetia marina) to a range of organosulfur SAMs. Furthermore, the extent of adhesion is dependent on the backbone structures and functional groups of the SAMs. The role of extracellular polymeric substances (EPS) in bacterial adhesion is also investigated. Pre‐conditioning experiments with cell‐free culture supernatants, containing planktonic EPS, allow quantification of the amount adsorbed onto surfaces and directly account for the impact of EPS adsorption on bacterial adhesion in the assay. While the physicochemical characteristics of the surfaces play a significant role in determining bacterial cell adhesion for low levels of conditioning by planktonic EPS, greater levels of conditioning by EPS reduce the difference between surfaces.
Morphing Origami Block for Lightweight Reconfigurable System

Origami provides a unique tool for the design of robotic frames owing to its simple shaping principle by “folding. ” However, achieving the fast and reversible activeness of a highly reconfigurable structure remains challenging owing to the limitations of accessible actuators. In particular, it is difficult to find an actuator that can realize a simultaneously large, rapid, reversible, and stable movement while leading to a favorable form factor for the origami. To overcome this, in this article, we propose a 3-D shape-shifting system consisting of a morphing origami block that complements the stability problem of shape memory alloy wire actuators by tuning its structural characteristics. This cooperative scheme improves the reversibility and stability of the shape-shifting system, which enables the rapid transformation with high degrees of freedom unlike in existing programmable origami. As a stand-alone unit of transformation, morphing block equipped with deployable mechanism and actuators weighs 6 g and has a volume change factor of ten. Furthermore, the transformation time in both directions is less than 5 s, and the block can carry more than 120 g of payload in the deployed state. The proposed system composed of multiple origami blocks can reconfigure itself into diverse 3-D target shapes.