Assessing the Impact of Delegation of Authority on Organizational Performance: Evidence from Twiga Chemical Industries Ltd | Book Publisher International

The study aimed at determining the effects of delegation of authority on organisational performance at Twiga Chemical Industries Ltd. The study was guided by four specific objectives, which include: determining the effects of legislative delegation, adjudicative delegation, monitoring and enforcement delegation and agenda setting delegation on performance at Twiga Chemical Industries Ltd. The study adopted a descriptive research design and a correlational research design. The target population in this study was 200 permanent employees of Twiga Chemical Industries Ltd in Nairobi. A stratified sampling technique was used in this study to come up with a desirable sample. Primary data was collected by use of questionnaires and utilised in this study to enhance the originality of the study. The questionnaires were administered to the randomly selected employees who were the respondents. The study used the quantitative method of data analysis. The collected data was edited, coded, keyed in and analysed using Statistical Package for Social Sciences (SPSS) version 20. The quantitative data was analysed using both descriptive statistics and correlations. A regression model was then used to show the relationship between the independent variables and the dependent variable. Regression of coefficients results showed that legislative delegation and organisation performance are positively and significantly related at both 1% and 5% confidence level (B=0.284, p=0.032). The results further indicated that adjudicative delegation and organisation performance are positively and significantly related at 1% and 5% confidence level (B=0.319, p=0.011). The results further established that monitoring and enforcement delegation were positively and significantly related at 1% and 5% confidence level (B=0.334, p=.013). Similarly, results showed that agenda setting, delegation and organisation performance were positively and insignificantly related at a 5% confidence level (B=0.094, p=0.455). Based on the findings, the study recommended that organisations and firms should consider the delegation of authority as one way of enhancing organisational performance. The study further recommended that those in authority should be very careful when delegating authority, not to go overboard.

 

Author (s) Details

Kennedy Akweyu Shikami
The Management University of Africa, Kenya.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-93-49970-52-6

Allan-Herndon-Dudley-Syndrome: An Overview of an Extremely Rare Disorder in Childhood | Chapter 8 | New Horizons of Science, Technology and Culture Vol. 2

 

Allan-Herndon-Dudley syndrome (AHDS) is a rare X-linked disease with severe neuropsychiatric abnormalities including psychomotor retardation, lack of speech development, dystonia, and severe intellectual deficits. William Allan, Florence C. Dudley, and C. Nash Herndon first described a syndrome which results from the disturbed formation of two thyroid hormone transporters, MCT8 and Oatp1c1. Nearly 320 individuals of around 130 families have been described so far with MCT-8 deficiency. The first individual treatment attempt with LT4 and Propylthiouracil was introduced in 2008; the development of therapies for Allan-Herndon-Dudley syndrome has gained momentum in recent years. Treatment options range from symptomatic interventions, including botulinum toxin injections, levodopa/carbidopa, assistive devices, functional therapies, rehabilitation to replacement therapies (LT3, LT4, DIPTA, TRIAC, TETRAC), and gene therapy. Diagnosis, treatment and cure of Allan-Herndon-Dudley syndrome in childhood remains challenging for the future. Due to the low number of cases, conducting large-scale studies is challenging, and therefore, it is difficult to find clear guidelines for this extremely rare disease in childhood.

 

 

Author(s) Details

Stefan Bittmann
Department of Pediatrics, Ped Mind Institute, Hindenburgring 4, D-48599 Gronau, Germany and Shangluo Vocational and Technical College, Shangluo, 726000, Shaanxi, China.

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5685

Unlocking Fingerprint Intelligence: Extracting Ridge, Minutiae, and DWT Features | Chapter 7 | New Horizons of Science, Technology and Culture Vol. 2

A fingerprint image captures the unique spatial pattern of ridges and valleys on the human fingertip, serving as a powerful and widely adopted A fingerprint image is a digital representation of the intricate and unique spatial configuration of ridges and valleys found on the human fingertip. These patterns are distinct for every individual and remain virtually unchanged throughout a person’s life, making fingerprints one of the most reliable forms of biometric identification. Their inherent individuality and permanence have made fingerprint recognition systems indispensable across a wide range of applications, including forensic investigations, national identity verification programs, secure access control systems, and personal device authentication.

 

This chapter, inspired by advancements in biometric sciences, anthropometry, and computational pattern recognition, investigates refined and more efficient methods of extracting rich and diverse features from fingerprint images. The emphasis lies on enhancing the accuracy and reliability of classification and identification tasks by focusing on extracting ridge information, minutiae patterns, and Discrete Wavelet Transform (DWT) features. These advanced features not only facilitate accurate fingerprint matching but also enable the derivation of soft biometric indicators such as gender, age, and potentially even blood type. This opens up promising avenues for the development of lightweight, non-invasive, and cost-effective biometric classification systems, which are particularly valuable in resource-constrained settings.

 

Fingerprint-based systems offer several key advantages over other biometric modalities, such as iris scans, facial recognition, or voice analysis. They typically require less storage space, involve simpler data acquisition procedures, and demand relatively low computational resources. These attributes make fingerprint recognition an ideal candidate for large-scale biometric applications, especially in densely populated or economically limited regions. The methodology explored in this chapter revolves around an automated framework that systematically analyses the spatial and structural features of fingerprints. It leverages both spatial domain and frequency domain analysis techniques to achieve a high-fidelity representation of fingerprint traits. By focusing on the precise extraction of ridge flows and minutiae points such as bifurcations and endings, and further enriching this representation with wavelet-based descriptors, the approach ensures robustness across various acquisition conditions, including variations in scanner types, resolutions, lighting conditions, and finger orientation.

 

Unlike traditional systems that rely solely on features such as ridge counts, thickness, and basic minutiae, the proposed approach employs enhanced feature extraction strategies that significantly improve identification accuracy. Through the application of Discrete Wavelet Transform, fingerprint images are analysed at multiple resolutions, enabling the capture of both global and fine-grained local details. This multiresolution capability allows the system to identify subtle fingerprint variations that might otherwise go undetected, making the overall classification more precise and resilient. Further, ridge structure is assessed in terms of quantifiable metrics like minimum, maximum, and average ridge lengths across the fingerprint. These measurements add another layer of distinguishing information, especially useful in scenarios where individuals have similar minutiae layouts but different ridge formations. In addition to these features, a rich set of minutiae descriptors-such as the number of ridge bifurcations, ridge endings, and total minutiae points-is extracted to enhance the discriminatory capability of the system.

 

By integrating these diverse features-spatial, geometric, and frequency-based-into a cohesive fingerprint recognition pipeline, this chapter presents a powerful and holistic approach to automated fingerprint classification. The comprehensive feature representation facilitates accurate and efficient matching of test fingerprint samples with stored templates, making the system suitable for use in high-security environments, law enforcement databases, and scalable authentication solutions.

 

In essence, this chapter contributes to the ongoing evolution of biometric technologies by introducing refined feature extraction techniques that enhance the reliability and versatility of fingerprint-based systems. The emphasis on improved accuracy, computational efficiency, and adaptability underscores the relevance of these techniques in shaping the future of secure and intelligent biometric identification.

 

Author(s) Details

 

Sayed Abulhasan Quadri
SECAB Institute of Engineering and Technology, Vijayapura, India.

 

Chandrakant P. Divate
SECAB Institute of Engineering and Technology, Vijayapura, India.

 

Tabasum Guledgudd
SECAB Institute of Engineering and Technology, Vijayapura, India.

 

Sayed Abdulhayan
PACE College, Mangalore, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5744

Determining Viscosity and Water Content of Silicate Melts from Melt Inclusion Data Using Stokes-Einstein Relation | Chapter 6 | New Horizons of Science, Technology and Culture Vol. 2

Silicate melts are the ubiquitous components of igneous processes in the Earth's crust and mantle and serve as the key transport agents for physico-chemical differentiation and evolution of the Earth. The viscosity is a fundamental property that influences the dynamic behaviour of silicate melts (melt segregation, magma mixing, crystal fractionation, fluid exsolution, the ascent rate of a magma). This study presents a new and straightforward method for estimating the viscosity and water content in hydrous silicate melts using homogenization measurements on melt inclusions in rock-forming minerals in granites and rhyolites from the Erzgebirge, the Slavkovsky les, Thuringia, the Caucasus, the Fichtelgebirge, and the Oberpfalz. A combination of the Stokes-Einstein equation and Shaw's (1972) viscosity calculation, along with data on temperature, inclusion diameter, run time, and inclusion chemistry, was employed. The viscosity at the minimum observable homogenization temperature is 3.6 * 104 Pa . s Generally, the water content ranges from 2.5 to 9 wt. %. The accuracy of the method and the potential for diffusive water loss are critically assessed.

 

The relationship between diffusion and viscosity, as described by the classic Stokes-Einstein relation, and the direct connection with viscosity (e.g., Shaw 1963) combine all-important physical quantities: temperature, time, length, and chemistry.

 

Author(s) Details

 

Rainer Thomas
Home Office Raman Laboratory, Im Waldwinkel 8, D-14662 Friesack, Germany.

 

Please see the book here: https://doi.org/10.9734/bpi/nhstc/v2/5750

Enhanced Image Protection Using Discrete Fractional Fourier Domain and Dual Random Phase Encoding | Chapter 5 | New Horizons of Science, Technology and Culture Vol. 2

In the digital era, secure image transmission is critical for applications ranging from medical imaging to military surveillance. Encryption is one of the well-known techniques to provide security in the transmission of multimedia content over the internet and wireless networks. There is use of image in all the areas, so its security is of great concern nowadays. In this paper, we propose a novel method of image encryption using discrete fractional Fourier transform (DFrFT) using an exponential random phase mask. The proposed method employs a two-phase masking approach, where the input image is first modulated with a random phase mask in the spatial domain and subsequently transformed using the DFrFT with tunable fractional orders. A second random phase mask is applied in the fractional frequency domain to further obscure image content. This technique makes it almost impossible to retrieve the image without using both the right keys. The combination of multidimensional DFrFT and random phase modulation significantly increases the key space and sensitivity to initial conditions, making brute-force and plaintext attacks computationally infeasible. Experimental results validate the robustness of the proposed method in terms of Peak Signal-to-Noise Ratio (PSNR) of maximum 42.02 dB, keyspace analysis for security, computational complexity same as FrFT, processing time 2.8654 seconds and mean square error -1.5735 dB obtained.

 

Author(s) Details

Deepak Sharma
Department of Electronics and Communication Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

Subodh Kumar Singhal
Department of Electronics and Communication Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

Prateek Pandey
Department of Computer Science Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5655

Safety Analysis of Cross-border Ferry Transportation: A Case Study of Batam–Singapore and Batam–Johor Routes | Chapter 4 | New Horizons of Science, Technology and Culture Vol. 2

As a border in Sumatra, Batam acts as a bridge between Indonesia and Singapore, and also Indonesia and Malaysia. Batam is located in locations strategic considering the sea border area, crossing between in Sumatra, Singapore and Johor, Malaysia. The objective of this study is to conduct a safety analysis of cross-border sea transportation between Indonesia, Singapore, and Malaysia. Specifically, this study assesses whether the ASEAN Economic Community, in order to facilitate ASEAN connectivity, since the 2015 application, has effectively facilitated safe and efficient maritime transportation. Because connectivity between ASEAN countries is considered an important part in the context of creating the implementation of the ASEAN economic community characterised by an open market in Southeast Asia, sea border transportation needs to develop again. This chapter adopted a case study approach that involves discussions of different facts of ferry routes between Batam – Singapore and also Batam – Johor, and gained information about the ferries, terminals and also the impact on the sea border transportation of three countries between Indonesia, Singapore and Malaysia. Terminal facilities and ferry operations were examined. Safety analysis of the ship is already fulfilled and satisfies the requirements of safety according to the Indonesian regulation.

 

Author(s) Details

Danny Faturachman
Marine Engineering Department, Darma Persada University, Jl. Taman Malaka Selatan, Pondok Kelapa, Jakarta Timur, 13450, Indonesia.

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5600

Development of Hydrogenated Amorphous Silicon (a-Si: H) Charge-Selective Contact Devices on a Polyimide Flexible Substrate for Dosimetry and Beam Flux Measurements | Chapter 3 | New Horizons of Science, Technology and Culture Vol. 2

Hydrogenated amorphous silicon (a-Si: H) devices on flexible substrates are currently being studied for application in dosimetry and beam flux measurements. The low deposition temperature of a-Si: H allows its layering on flexible materials like polyimide (PI). The necessity of in vivo dosimetry requires thin devices with maximal transparency and flexibility. For this reason, a thin (<10 µm) a-Si: H device deposited on a thin polyimide sheet is a very valid option for this application. Furthermore, a-Si: H is a material that has an intrinsically high radiation hardness. In order to develop these devices, the HASPIDE (Hydrogenated Amorphous Silicon Pixel Detectors) collaboration has implemented two different device configurations: n-i-p type diodes and charge-selective contact devices. Charge-selective contact devices are based on a three-layer structure featuring a thin layer of metal-oxides with a small activation energy (like TiO2), a thick layer of intrinsic a-Si: H, and a thin layer of metal-oxides with a large activation energy (like MoOx or WOx). Charge-selective contact-based devices have been studied for solar cell applications, and recently, the above-mentioned collaboration has tested these devices for X-ray dose measurements. In this paper, the HASPIDE collaboration has studied the X-ray and proton response of charge-selective contact devices deposited on Polyimide.

 

The linearity of the photocurrent response to X-ray versus dose rate has been assessed at various bias voltages. The sensitivity to protons has also been studied at various bias voltages, and the wide range linearity has been tested for fluxes in the range from 8.3 × 107 to 2.49 × 1010 p/(cm2 s). The results show a very good linearity in the dose rate range tested, in addition to a good sensitivity and quite low leakage current below 4 V bias. Dosimetric sensitivity is related to bias voltage, in a very linear behaviour.

 

Author(s) Details

Mauro Menichelli

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Saba Aziz

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Aishah Bashiri

Centre for Medical Radiation Physics, University of Wollongong, Northfields Ave., Wollongong, NSW 2522, Australia and Physics Department, Faculty of Science and Art, Najran University, King Abdulaziz Rd,1988 Najran, Saudi Arabia.

Marco Bizzarri

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipipartimento di Fisica e Geologia, dell’Università degli Studi di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Clarissa Buti

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, Viale Morgagni 50, 50135 Firenze, Italy.

 

 Lucio Calcagnile

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Daniela Calvo

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy.

 

Mirco Caprai

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Domenico Caputo

INFN Sezione di Roma 1, Piazzale Aldo Moro 2, 00185 Roma, Italy and Dipartimento Ingegneria dell’Informazione, Elettronica e Telecomunicazioni, dell’Università degli studi di Roma, Via Eudossiana, 18, 00184 Roma, Italy.

 

Anna Paola Caricato

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Roberto Catalano

INFN Laboratori Nazionali del Sud, Via S.Sofia62, 95123 Catania, Italy.

 

Massimo Cazzanelli

Dipatimento di Ingegneria, TIFPA and Trento University, Via Sommarive 14, 38123 Povo, Italy.

 

Roberto Cirio

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy.

 

Giuseppe Antonio Pablo Cirrone

INFN Laboratori Nazionali del Sud, Via S.Sofia62, 95123 Catania, Italy.

 

Federico Cittadini

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipatimento Di Fisica e Astronomia, dell’Università di Padova, Via Marzolo 8, 35131 Padova, Italy.

 

Tommaso Croci

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipatimento di Ingegneria, dell’Università degli studi di Perugia, Via G.Duranti, 06125 Perugia, Italy.

 

Giacomo Cuttone

INFN Laboratori Nazionali del Sud, Via S.Sofia62, 95123 Catania, Italy.

 

Giampiero de Cesare

INFN Sezione di Roma 1, Piazzale Aldo Moro 2, 00185 Roma, Italy and Dipartimento Ingegneria dell’Informazione, Elettronica e Telecomunicazioni, dell’Università degli studi di Roma, Via Eudossiana, 18, 00184 Roma, Italy.

 

Paolo De Remigis

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy.

 

Sylvain Dunand

Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Electrical and Microengineering (IME), Rue de la Maladière 71b, 2000 Neuchâtel, Switzerland.

 

Michele Fabi

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and DiSPeA, Università di Urbino Carlo Bo, 61029 Urbino, Italy.

 

Luca Frontini

INFN Sezione di Milano Via Celoria 16, 20133 Milano, Italy and Dipartimento di Fisica, dell’Università degli Studi di Milano, Via Celoria 16, 20133 Milano, Italy.

 

 

Catia Grimani

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and DiSPeA, Università di Urbino Carlo Bo, 61029 Urbino, Italy.

 

Mariacristina Guarrera

INFN Laboratori Nazionali del Sud, Via S.Sofia62, 95123 Catania, Italy.

 

Hamza Hasnaoui

Dipatimento di Ingegneria, TIFPA and Trento University, Via Sommarive 14, 38123 Povo, Italy.

 

Maria Ionica

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy

 

Keida Kanxheri

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipipartimento di Fisica e Geologia, dell’Università degli Studi di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Matthew Large

Centre for Medical Radiation Physics, University of Wollongong, Northfields Ave., Wollongong, NSW 2522, Australia.

 

Francesca Lenta

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy and Politecnico di Torino Facoltà di Ingegneria, Corso Duca degli Abruzzi 24, 10129 Torino, Italy.

 

Valentino Liberali

INFN Sezione di Milano Via Celoria 16, 20133 Milano, Italy and Dipartimento di Fisica, dell’Università degli Studi di Milano, Via Celoria 16, 20133 Milano, Italy.

 

 

Nicola Lovecchio

INFN Sezione di Roma 1, Piazzale Aldo Moro 2, 00185 Roma, Italy and Dipartimento Ingegneria dell’Informazione, Elettronica e Telecomunicazioni, dell’Università degli studi di Roma, Via Eudossiana, 18, 00184 Roma, Italy.

 

Maurizio Martino

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Giuseppe Maruccio

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Giovanni Mazza

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy.

 

Anna Grazia Monteduro

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Arianna Morozzi

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Augusto Nascetti

INFN Sezione di Roma 1, Piazzale Aldo Moro 2, 00185 Roma, Italy and Scuola di Ingegneria Aerospaziale, Università degli studi di Roma, Via Salaria 851/881, 00138 Roma, Italy.

 

Stefania Pallotta

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, Viale Morgagni 50, 50135 Firenze, Italy.

 

Andrea Papi

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Daniele Passeri

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipatimento di Ingegneria, dell’Università degli studi di Perugia, Via G.Duranti, 06125 Perugia, Italy.

 

Maddalena Pedio

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and CNR-IOM, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Marco Petasecca

Centre for Medical Radiation Physics, University of Wollongong, Northfields Ave., Wollongong, NSW 2522, Australia.

 

Giada Petringa

INFN Laboratori Nazionali del Sud, Via S.Sofia62, 95123 Catania, Italy.

 

Francesca Peverini

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipipartimento di Fisica e Geologia, dell’Università degli Studi di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Pisana Placidi

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and Dipatimento di Ingegneria, dell’Università degli studi di Perugia, Via G.Duranti, 06125 Perugia, Italy.

 

 

Matteo Polo

Dipatimento di Ingegneria, TIFPA and Trento University, Via Sommarive 14, 38123 Povo, Italy

 

Alberto Quaranta

Dipatimento di Ingegneria, TIFPA and Trento University, Via Sommarive 14, 38123 Povo, Italy.

 

Gianluca Quarta

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Silvia Rizzato

INFN Sezione di Lecce, Dipartimento di Fisica e Matematica, dell’Università del Salento, Via per Arnesano, 73100 Lecce, Italy.

 

Federico Sabbatini

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy.

 

Leonello Servoli

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

 

Alberto Stabile

INFN Sezione di Milano Via Celoria 16, 20133 Milano, Italy and Dipartimento di Fisica, dell’Università degli Studi di Milano, Via Celoria 16, 20133 Milano, Italy.

 

Cinzia Talamonti

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence, Viale Morgagni 50, 50135 Firenze, Italy.

 

Jonathan Emanuel Thomet

Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Electrical and Microengineering (IME), Rue de la Maladière 71b, 2000 Neuchâtel, Switzerland.

 

Luca Tosti

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy.

Monica Setia Vasquez Mora

INFN Sezione di Milano Via Celoria 16, 20133 Milano, Italy.

Mattia Villani

INFN Sezione di Firenze, Via Sansone 1, 50019 Sesto Fiorentino, Italy and DiSPeA, Università di Urbino Carlo Bo, 61029 Urbino, Italy.

 

Richard James Wheadon

INFN Sezione di Torino Via Pietro Giuria, 110125 Torino, Italy.

 

Nicolas Wyrsch

Ecole Polytechnique Fédérale de Lausanne (EPFL), Institute of Electrical and Microengineering (IME), Rue de la Maladière 71b, 2000 Neuchâtel, Switzerland.

 

Nicola Zema

INFN, Sezione di Perugia, Via Pascoli s.n.c., 06123 Perugia, Italy and CNR Istituto Struttura Della Materia, Via Fosso del Cavaliere 100, 00133 Roma, Italy.

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5651