bluuebunny/crossref_metadata_2025 huggingface dataset:
An MRI-Based Clinical-Perfusion Model Predicts Pathological Subtypes of Prevascular Mediastinal Tumors
Authors: Lin Chia-Ying , Yen Yi-Ting , Huang Li-Ting , Chen Tsai-Yun , Liu Yi-Sheng , Tang Shih-Yao , Huang Wei-Li , Chen Ying-Yuan , Lai Chao-Han , Fang Yu-Hua Dean , Chang Chao-Chun , Tseng Yau-Lin
Published: April 2022

This study aimed to build machine learning prediction models for predicting pathological subtypes of prevascular mediastinal tumors (PMTs). The candidate predictors were clinical variables and dynamic contrast–enhanced MRI (DCE-MRI)–derived perfusion parameters. The clinical data and preoperative DCE–MRI images of 62 PMT patients, including 17 patients with lymphoma, 31 with thymoma, and 14 with thymic carcinoma, were retrospectively analyzed. Six perfusion parameters were calculated as candidate predictors. Univariate receiver-operating-characteristic curve analysis was performed to evaluate the performance of the prediction models. A predictive model was built based on multi-class classification, which detected lymphoma, thymoma, and thymic carcinoma with sensitivity of 52.9%, 74.2%, and 92.8%, respectively. In addition, two predictive models were built based on binary classification for distinguishing Hodgkin from non-Hodgkin lymphoma and for distinguishing invasive from noninvasive thymoma, with sensitivity of 75% and 71.4%, respectively. In addition to two perfusion parameters (efflux rate constant from tissue extravascular extracellular space into the blood plasma, and extravascular extracellular space volume per unit volume of tissue), age and tumor volume were also essential parameters for predicting PMT subtypes. In conclusion, our machine learning–based predictive model, constructed with clinical data and perfusion parameters, may represent a useful tool for differential diagnosis of PMT subtypes.
Combined Hepatocellular-Cholangiocarcinoma: What the Multidisciplinary Team Should Know
Authors: Cutolo Carmen , Dell’Aversana Federica , Fusco Roberta , Grazzini Giulia , Chiti Giuditta , Simonetti Igino , Bruno Federico , Palumbo Pierpaolo , Pierpaoli Luca , Valeri Tommaso , Izzo Francesco , Giovagnoni Andrea , Grassi Roberto , Miele Vittorio , Barile Antonio , Granata Vincenza
Published: April 2022

Combined hepatocellular-cholangiocarcinoma (cHCC-CCA) is a rare type of primary liver malignancy. Among the risk factors, hepatitis B and hepatitis C virus infections, cirrhosis, and male gender are widely reported. The clinical appearance of cHCC-CCA is similar to that of HCC and iCCA and it is usually silent until advanced states, causing a delay of diagnosis. Diagnosis is mainly based on histology from biopsies or surgical specimens. Correct pre-surgical diagnosis during imaging studies is very problematic and is due to the heterogeneous characteristics of the lesion in imaging, with overlapping features of HCC and CCA. The predominant histological subtype within the lesion establishes the predominant imaging findings. Therefore, in this scenario, the radiological findings characteristic of HCC show an overlap with those of CCA. Since cHCC-CCAs are prevalent in patients at high risk of HCC and there is a risk that these may mimic HCC, it is currently difficult to see a non-invasive diagnosis of HCC. Surgery is the only curative treatment of HCC-CCA. The role of liver transplantation (LT) in the treatment of cHCC-CCA remains controversial, as is the role of ablative or systemic therapies in the treatment of this tumour. These lesions still remain challenging, both in diagnosis and in the treatment phase. Therefore, a pre-treatment imaging diagnosis is essential, as well as the identification of prognostic factors that could stratify the risk of recurrence and the most adequate therapy according to patient characteristics.
Carcinoma of Unknown Primary (CUP) versus CUP Turned to Primary Carcinoma of the Head and Neck—An Analysis of Diagnostic Methods and the Impact of Primary Tumor on Clinical Outcome
Authors: Faisal Muhammad , Le Nguyen-Son , Grasl Stefan , Janik Stefan , Simmel Helmut , Schratter-Sehn Annemarie U. , Hamzavi Jafar-Sasan , Franz Peter , Erovic Boban M.
Published: April 2022

Background. The purpose of this study was to analyze the value of different diagnostic methods in detecting the primary site and the impact of primary tumors on the clinical outcome of carcinoma of unknown primary (CUP). Methods. In this multicenter, retrospective study, 124 patients with true CUP (n = 94) and CUP turned to primary carcinoma (n = 30) were included. Patients with evidence of primary site during the clinical examination were excluded a priori. The diagnostic procedure was comprised of imaging and invasive methods (fine-needle-aspiration, tonsillectomy and panendoscopy). All patients were treated with curative intent. Results. Despite extensive diagnostic workup, the primary site remained unknown in 75.8%. Invasive diagnostic methods showed higher primary detection rates than imaging modalities (15.1% vs. 7.8%). Tonsillectomy and panendoscopy revealed the primary tumor in 14.9% and 15.2% of patients, whereas the detection rates of CT, MRI and FDG-PET-CT were 10.1%, 4.8% and 6.5%, respectively. The occurrence of primary tumors led to a significantly deteriorating 5-year overall survival (p = 0.002) and emerged as survival prognosticator (HR = 2.764, p = 0.003). Conclusion. Clinical examination in combination with tonsillectomy and panendoscopy was superior to imaging alone in detecting the primary tumor. When the CUP of patients turned to a primary tumor, clinical outcome was significantly worse than in CUP patients.
Discrete Infomax Codes for Supervised Representation Learning
Authors: Lee Yoonho , Kim Wonjae , Park Wonpyo , Choi Seungjin
Published: April 2022

For high-dimensional data such as images, learning an encoder that can output a compact yet informative representation is a key task on its own, in addition to facilitating subsequent processing of data. We present a model that produces discrete infomax codes (DIMCO); we train a probabilistic encoder that yields k-way d-dimensional codes associated with input data. Our model maximizes the mutual information between codes and ground-truth class labels, with a regularization which encourages entries of a codeword to be statistically independent. In this context, we show that the infomax principle also justifies existing loss functions, such as cross-entropy as its special cases. Our analysis also shows that using shorter codes reduces overfitting in the context of few-shot classification, and our various experiments show this implicit task-level regularization effect of DIMCO. Furthermore, we show that the codes learned by DIMCO are efficient in terms of both memory and retrieval time compared to prior methods.
A New Strategy in Boosting Information Spread
Authors: Zhang Xiaorong , Liu Sanyang , Gong Yudong
Published: April 2022

Finding a seed set to propagate more information within a specific budget is defined as the influence maximization (IM) problem. The traditional IM model contains two cardinal aspects: (i) the influence propagation model and (ii) effective/efficient seed-seeking algorithms. However, most of models only consider one kind of node (i.e., influential nodes), ignoring the role of other nodes (e.g., boosting nodes) in the spreading process, which are irrational. Specifically, in the real-world propagation scenario, the boosting nodes always improve the spread of influence from the initial activated seeds, which is an efficient and cost-economic measure. In this paper, we consider the realistic budgeted influence maximization (RBIM) problem, which contains two kind of nodes to improve the diffusion of influence. Facing the newly modified objective function, we propose a novel B-degree discount algorithm to solve it. The novel B-degree discount algorithm which adopts the cost-economic boosting nodes to retweet the influence from the predecessor nodes can greatly reduce the cost, and performs better than other state-of-the-art algorithms in both effect and efficiency on RBIM problem solving.
Preference-Tree-Based Real-Time Recommendation System
Authors: Kang Seongju , Chung Kwangsue
Published: April 2022

In the current era of online information overload, recommendation systems are very useful for helping users locate content that may be of interest to them. A personalized recommendation system presents content based on information such as a user’s browsing history and the videos watched. However, information filtering-based recommendation systems are vulnerable to data sparsity and cold-start problems. Additionally, existing recommendation systems suffer from the large overhead incurred in learning regression models used for preference prediction or in selecting groups of similar users. In this study, we propose a preference-tree-based real-time recommendation system that uses various tree models to predict user preferences with a fast runtime. The proposed system predicts preferences based on two balance constants and one similarity threshold to recommend content with a high accuracy while balancing generalized and personalized preferences. The results of comparative experiments and ablation studies confirm that the proposed system can accurately recommend content to users. Specifically, we confirmed that the accuracy and novelty of the recommended content were, respectively, improved by 12.1% and 27.2% compared to existing systems. Furthermore, we verified that the proposed system satisfies real-time requirements and mitigates both cold-start and overfitting problems.
Do Corporate Governance and Gender Diversity Matter in Firm Performance (ROE)? Empirical Evidence from Jordan
Authors: Alshirah Malek Hamed , Alfawareh Faraj Salman , Alshira’h Ahmad Farhan , Al-Eitan Ghaith , Bani-Khalid Tareq , Alsqour Moh’d
Published: April 2022

The aim of this paper was to examine the effect of managerial/board gender diversity and corporate governance structure on firm performance in a Jordanian business environment—a developing economy that has a distinct environment from that of developed economies. The current study focuses on the unique context of an emerging economy (i.e., Jordan). Data were collected from nonfinancial companies listed on the Amman Stock Exchange from 2018 to 2020. Data analysis was carried out using the random-effects estimator, which was considered as the most suitable for this study. The results disclose that female representation on the board of executives of Jordanian companies had a positive but insignificant effect on corporate performance, as measured by the return on equity, indicating that this variable has no effect on the performance of firms in Jordan. Both family ownership and board size had negative significant effects on performance, but for the moderating effect, corporate governance structure had no effect on the relationship among CEO duality, institution ownership, government ownership, independent directors, and firm performance. The current study only focused on Jordanian industrial firms listed on ASE, thus rendering the findings nongeneralizable to other sectors and nations. Further investigations are urged to broaden the context of the study to achieve more enriched findings. Managers can use the findings to achieve a deeper understanding of the way governance structure affects firm performance. Additionally, regulators at the Jordan Securities Commission can attain valuable insight about the adequacy of the current regulations regarding the role of gender diversity and corporate governance structure in Jordan. The current study contributes to the literature concerning the effect of managerial gender diversity and corporate governance structure on performance. Furthermore, this investigation aims to fill the current research gap in the context of Jordan, which is an emerging economy in the Arab region that is under-represented in this field of research.
School Organizational Culture and Leadership: Theoretical Trends and New Analytical Proposals
Authors: Torres Leonor L.
Published: April 2022

Various changes in the spheres of education policy and school management over recent decades have sparked a renewed interest in the issue of school culture and its potential to understand processes of leadership and academic performance. What are the contributions and potentialities of organizational culture for understanding school organizations and their leadership processes? This article has two goals: (i) to identify trends and theoretical particularities inherent to the major approaches to organizational culture, focusing on research carried out in the school setting; (ii) to debate the heuristic usefulness of a theoretical proposal for studying organizational culture in the school setting. The article presents a multidimensional analysis of school organizational culture, considering political, social and educational factors, aiming to capture the unique nature of school cultures and their links to processes of leadership and management. By linking these to different leadership perspectives, this model may inspire further comparative study of educational management in an international context. This approach demonstrates the need to tailor models for analysing organizational culture to the school environment, to achieve a deeper and more solid understanding of school life and leadership and management phenomena.
Transversal Competencies for Employability: From Higher Education to the Labour Market
Authors: Belchior-Rocha Helena , Casquilho-Martins Inês , Simões Eduardo
Published: April 2022

Aligning learning goals with the needs of the labour market is a difficult task for universities, especially in the present day. Although organisations seek professionals with flexible and varied skills, universities often underestimate the importance of cross-curricular skills. Thus, this article aims to identify the perception of recent graduates as to the importance of the transversal skills that they acquired and developed at university and the ways in which they are now applied in the work environment. In this exploratory study, we sent a questionnaire to recent graduates that allowed us to analyse the development and applicability of these competencies in organisations. The results are further discussed within the broader framework of how universities adapt to the strong socio-economic challenges that characterise current times and the integration of recent graduates into the labour market.
Determining the Learning Profile of Engineering Projects Students from Their Characteristic Motivational Profile
Authors: Botejara-Antúnez Manuel , Sánchez-Barroso Gonzalo , González-Domínguez Jaime , García-Sanz-Calcedo Justo
Published: April 2022

Engineering courses usually have a low success rate, and students that take them often consider them difficult and show little motivation towards them. In this context, it is essential to obtain information about the profile of the students so that the teaching can be adapted to their perceived needs and motivations as well to provide support to them. This descriptive-exploratory research study was carried out to determine the learning profile of engineering project students through their motivational profile based on five grouping variables (gender, type of high school of origin, access studies, specialty, repeater). The instrument used was a consolidated motivational assessment questionnaire consisting of items in a series of seven basic scales aligned and grouped together into three motivational dimensions (MAPE-3). As a result, a student profile was observed that was dominated by the dimension of motivation towards the task and characterized by a mixed reflective-practical learning profile based on analytical and predominantly practical individuals.
Boosting Social Spam Detection via Attention Mechanisms on Twitter
Authors: Shen Hua , Liu Xinyue , Zhang Xianchao
Published: April 2022

Twitter is one of the largest social networking platforms, which allows users to make friends, read the latest news, share personal ideas, and discuss social issues. The huge popularity of Twitter mean it attracts a lot of online spammers. Traditional spam detection approaches have shown the effectiveness for identifying Twitter spammers by extracting handcrafted features and training machine learning models. However, such models need knowledge from domain experts. Moreover, the behaviors of spammers can change according to the defense strategies of Twitter. These result in the ineffectiveness of the traditional feature-based approaches. Although deep-learning-based approaches have been proposed for detecting Twitter spammers, they all treat each tweet equally, and ignore the differences among them. To solve these issues, in this paper, we propose a new attention-based deep learning model to detect social spammers in Twitter. In particular, we first introduce the state-of-the-art pretraining model BERTweet for learning the representation of each tweet, and then use the proposed novel attention-based mechanism to learn the user representations by distinguishing the differences among tweets posted by each user. Moreover, we take social interactions into consideration and propose that a graph attention network is used to update the learned user representations, to further improve the accuracy of identifying spammers. Experiments on a publicly available, real-world Twitter dataset show the effectiveness of the proposed model, which is able to significantly enhance the performance.
Performance Enhancement of Functional Delay and Sum Beamforming for Spherical Microphone Arrays
Authors: Zhao Yang , Chu Zhigang , Li Linyong
Published: April 2022

Functional delay and sum (FDAS) beamforming for spherical microphone arrays can achieve 360° panoramic acoustic source identification, thus having broad application prospects for identifying interior noise sources. However, its acoustic imaging suffers from severe sidelobe contamination under a low signal-to-noise ratio (SNR), which deteriorates the sound source identification performance. In order to overcome this issue, the cross-spectral matrix (CSM) of the measured sound pressure signal is reconstructed with diagonal reconstruction (DRec), robust principal component analysis (RPCA), and probabilistic factor analysis (PFA). Correspondingly, three enhanced FDAS methods, namely EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA, are established. Simulations show that the three methods can significantly enhance the sound source identification performance of FDAS under low SNRs. Compared with FDAS at SNR = 0 dB and the number of snapshots = 1000, the average maximum sidelobe levels of EFDAS-DRec, EFDAS-RPCA, and EFDAS-PFA are reduced by 6.4 dB, 21.6 dB, and 53.1 dB, respectively, and the mainlobes of sound sources are shrunk by 43.5%, 69.0%, and 80.0%, respectively. Moreover, when the number of snapshots is sufficient, the three EFDAS methods can improve both the quantification accuracy and the weak source localization capability. Among the three EFDAS methods, EFDAS-DRec has the highest quantification accuracy, and EFDAS-PFA has the best localization ability for weak sources. The effectiveness of the established methods and the correctness of the simulation conclusions are verified by the acoustic source identification experiment in an ordinary room, and the findings provide a more advanced test and analysis tool for noise source identification in low-SNR cabin environments.
Quad-Band Circular Polarized Antenna for GNSS, 5G and WIFI-6E Applications
Authors: Liu Xiaoming , Wang Haiyang , Yang Xiaofan , Wang Jinhong
Published: April 2022

A quad-band circularly-polarized antenna, for applications of a global navigation satellite system (GNSS), 5G, and WIFI-6E, is designed, fabricated, and measured. The proposed antenna is formed by an L-shaped radiator, a rectangular frame ground with an L-shaped stub, and a rectangular strip at the opposite corner. The microstrip antenna can generate four frequency bands, covering WIFI-6E (5925–7125 MHz), 5G n77 (3300–4200 MHz), n78 (3300–3800 MHz), and the GNSS bands. This antenna generates right hand circular polarization (RHCP) waves in the low frequency band (0.95–2.11 GHz), covering GPS, BDS, GLONASS, and GALILEO applications. Moreover, an L-shaped aperture and three rectangular slits are cut on the ground to broaden the axial-ratio bandwidth at the upper band. A prototype is fabricated and measured to verify the performance of this design. It is shown that the agreement between the simulation and measurement is satisfactorily good. The measured −10 dB bandwidths for each band are 75.8% (0.95–2.11 GHz), 55.8% (3.05–5.39 GHz), 39.9% (5.84–8.19 GHz) and 10.3% (9.14–10.68 GHz), respectively. While the measured 3 dB axial-ratio bandwidths are 59.4% (1.16–2.14 GHz), 35.8% (3.23–4.64 GHz), 8.4% (5.70–6.20 GHz), and 2.6% (7.51–7.71 GHz), the measured gains are 4.56, 2.28, 4.26, and 4.30 dBi at 1.5 GHz, 3.8 GHz, 6 GHz, and 7.6 GHz, respectively.
Correlation Technologies for Emerging Wireless Applications
Authors: Wane Sidina , Ferrero Fabien , Dinh Thanh Vinh , Bajon Damienne , Duvillaret Lionel , Gaborit Gwenaël , Huard Vincent
Published: April 2022

In this article, we introduce correlation technologies both at RF/mmWave and baseband frequencies. At RF and mmWave frequencies, power-spectra and energy-spectra metrics are introduced for measuring the power-density of mobile devices and systems. New ASIC-embedded smart connectors are developed for bringing correlation-based signal processing close to antenna modules. At baseband frequencies, DSP-based convolutional accelerators are proposed for fast and accurate measurement of EVM (error vector magnitude) using correlation technologies. Porting of the DSP-based convolutional accelerators into advanced fully depleted silicon-on-insulator (FDSOI)-based ASIC platforms for co-integration with adaptive RF/mmWave front-end modules will enable real-time extraction of auto-correlation and cross-correlation functions of stochastic signals. Perspectives for optically synchronized interferometric-correlation technologies are drawn for accurate measurements in noisy environments of stochastic EM fields using power-spectra and energy-spectra metrics. Adoption of correlation technologies will foster new paradigms relative to interactions of humans with smart devices and systems in randomly fluctuating environments. The resulting new paradigms will open new possibilities in communication theory for properly combining and reconciling information signal theory (Shannon information-based entropy) and physical information theory (statistical-physics-based entropy) into a unified framework.
A Non-Isolated DC-DC Modular Multilevel Converter with Proposed Middle Cells
Authors: Huang Ming
Published: April 2022

Unlike the modular multilevel converter (MMC) topology operated under the rectifier or inverter modes, control of the balanced state for the submodule (SM) capacitor voltage has emerged as the key issue for DC-DC MMCs. This is mainly caused by no balanced alternative powers being used for balancing SM capacitor voltages, which can be absorbed from the input or output DC sides of the converter. Typically, the alternative voltages and currents should be injected to achieve SM capacitor voltage balance in the DC-DC MMC. However, this solution is based on the cost of adopting the bulky LC filter components. For interconnecting different DC voltages in medium-voltage applications, this paper presents a non-isolated DC-DC MMC equipped with the proposed middle cells. It is intended to achieve DC voltage conversion without adopting bulky passive LC filters. On the one hand, the alternative currents, used for balancing the SM capacitor voltages, are arranged for flowing only within the phase legs of the proposed DC-DC MMC without disturbing the input current. On the other hand, through appropriate control of the middle cells, compensated components can be developed to eliminate the undesirable voltages on the output DC side. The middle cells of the proposed DC-DC MMC are supplied with the function of the active filter, which enables the DC-DC MMC system to escape the bulky LC components. Through theoretical analysis and a control strategy, the proposed DC-DC MMC has been analyzed comprehensively. Finally, the simulation and experimental results are verified to evaluate the effectiveness of the proposed DC-DC MMC.
Gain Function-Based Visual Tracking Control for Inertial Stabilized Platform with Output Constraints and Disturbances
Authors: Liu Xiangyang , Yang Jun , Qiao Pengyu
Published: April 2022

In this paper, a composite control strategy is proposed to deal with output constraints and disturbances of the visual tracking system for an inertial stabilized platform, which combines active disturbance compensation and the variable gain function technique. Firstly, the model of system considering multi-source disturbances is established, where the controlled output is the constrained position of the target in the image plane. Secondly, in order to avoid the tracked target being lost in the field of view of the camera, a control method based on the variable gain function technique is designed to ensure that the controlled output remains within the feasible range. Moreover, the active disturbance estimation and compensation method is introduced to improve the anti-disturbance ability of the system under the situation of small output error, obtaining satisfactory tracking performance. The stability analysis and the proof of constrained output are given following the controller design. Finally, results of simulation and experiments are shown to illustrate the promised advantages of the proposed composite control approach.
Extraction of Rice Bran Oil Using CO2-Expanded Hexane in the Two-Phase Region
Authors: Okajima Idzumi , Ito Kaichi , Aoki Yusuke , Kong Chang Yi , Sako Takeshi
Published: April 2022

The performance of CO2-expanded hexane in the vapor-liquid two-phase region was examined to extract phosphorus-free bio-oil from rice bran. Previously, it was found that in the uniform liquid phase region, it is difficult to maintain the phosphorus concentration at a stable and low level when the CO2 mole fraction changed slightly. To overcome this issue, the dependences of the phosphorus and free fatty acid concentrations, the oil solubility, and the oil yield on the CO2 mole fraction in the CO2-expanded hexane were measured at 25 °C, 5.1–5.2 MPa, and at a CO2 mole fraction of 0.88–0.94 in the two-phase region. Thus, a relatively constant phosphorus concentration of <10 ppm was maintained in the extracted oil, which was ~1/50 of that in the oil extracted by hexane, thereby satisfying the European unified standard for biodiesel fuel. Furthermore, a high oil yield exceeding that of hexane extraction was maintained over all CO2 mole fractions. Moreover, the oil solubility in the CO2-expanded hexane decreased linearly with the CO2 mole fraction, and so this factor represented the oil-dissolving power of the extractant more accurately than the oil yield used previously. The free fatty acid concentration was 83% of that extracted by hexane.
Pitfalls of Using Biomarker Maturity Parameters for Organic Matter Maturity Assessment Suggested by Coal Hydrous Pyrolysis
Authors: Yin Mengsha , Huang Haiping
Published: April 2022

Crude oil maturity assessment is a vital goal for petroleum geochemistry, and equally important is the exploration of maturity indicators of sufficient credibility. While most molecular proxy parameters have been extensively used and have provided some useful insights; the component ratios approach is somewhat limited in validity regarding oil maturity characterization for variable reasons. Novel thermal trends of hopanes and steranes were observed in a series of hydrous pyrolysates of an immature coal (0.49 %Ro) generated at eight target temperatures ranging from 250–375 °C (measured vitrinite reflectance of 0.71–0.91 %Rm), which–further substantiated this idea. Expelled oil and extractable bitumen were combined as the total soluble organic material (tSOM) for each pyrolysis experiment to mitigate the effects of primary expulsion fractionation. While bitumen extracted from the original coal—the 250 °C tSOM—the 275 °C tSOM (0.49–0.73 %Rm) sequence recorded normal increases in C31 αβ-hopane 22S/(22S + 22R) and decreases in C29–C30 βα-moretane/αβ-hopane ratios, low values and continuous decreases in C29 5α-sterane 20S/(20S + 20R) and ββ/(αα + ββ), Ts/(Ts + Tm) and C29Ts/(C29Ts + C29 αβ-hopane) suggested no biomarker thermal isomerization but predominant control from precursor-to-biomarker transformation. Continuous increases in 22S/(22S + 22R) until 1.43 %Rm accorded with thermal isomerization, but a delayed ratio equilibration at 1.43 %Rm again suggested biomarker precursor interference, which also played a role in the reductions in 20S/(20S + 20R) and ββ/(αα + ββ) to 0.9 %Rm, whereas increasing and high values of C29–C30 βα-moretane/αβ-hopane ratios occurring during 0.73–1.43 %Rm. Reversals in 22S/(22S + 22R) and fluctuations in 20S/(20S + 20R) and ββ/(αα + ββ) at elevated maturity levels with minimum yields of biomarker precursors were predominantly controlled by differential isomer degradative rates. These rarely reported thermal distribution patterns of biomarkers illustrated very complicated biomarker generation–destruction processes during maturation and suggested that the release of bond biomarker to the free status may govern the biomarker maturity ratios rather than thermal isomerization. While the rapid heating conditions and high temperatures in pyrolysis differ inevitably from natural evolution under geological conditions, our study unveiled that unusual biomarker ratios in geological samples could be the norm, contradictory to common beliefs. Accordingly, we propose that isomer concentration is an essential tool to validate maturity estimation of organic matter by isomer ratios, especially for highly mature oils and sediment extracts.
Experimental Validation and Numerical Simulation of a Hybrid Sensible-Latent Thermal Energy Storage for Hot Water Provision on Ships
Authors: Frazzica Andrea , Manzan Marco , Palomba Valeria , Brancato Vincenza , Freni Angelo , Pezzi Amedeo , Vaglieco Bianca M.
Published: April 2022

In this study, the development and testing of a hybrid thermal energy storage (TES) including phase change material (PCM) macro-capsules inside a vertical sensible tank is presented. The storage was specifically developed for delivering hot water on board of ships. Accordingly, a commercial PCM was selected and tested. Subsequently, the hybrid TES was designed and tested under mimicked boundary conditions at lab scale, showing the possibility of increasing the volumetric energy storage density up to 30% compared to the sensible configuration. On this basis, two numerical models were developed: a detailed one, implemented in a Fluent environment, aiming at investigating the main parameters affecting the heat transfer efficiency inside the TES and a second one, implemented in an ESP-r environment to simulate the TES as a component to be implemented inside a more complex system, thus helping its accurate design and operation through a reliable modelling phase. Both models were satisfactorily validated against the experimental results, thus being made available for future investigations and design optimization.
The Development of Citizen-Installed Renewable Energy Capacities in Former Eastern Bloc Countries—The Case of Poland
Authors: Schwanitz Valeria Jana , Rudek Tadeusz Józef , Hubert Wit , Wierling August Hubert
Published: April 2022

We confront empirical data on citizen-led renewable energy capacities in Poland with results obtained from a meta-theoretical, empirical analysis of the national energy system. We elicit and rank essential disabling and enabling factors that explain the current low level of citizen energy in Poland. Altogether, we estimate the contributions of individual and collective prosumers as amounting to about 3.2 GW, with PV installations contributing more than 90%. Most activities are rather recent and come from individual prosumers. The factors with the greatest explanatory power are connected with decades of a rigid, centralized Polish energy system going hand in hand with social, regulatory, and technical lock-ins. Strikingly, factors connected with the heritage of, and transition from, the socialist period are less important, but they do explain why substantially more contributions originate from individuals compared to collective prosumers. Our results show that the currently rather small size of citizen-installed renewable capacities and the modest number of collective initiatives in Poland are due to several barriers. This paper summarizes them and provides a novel scientific method of ranking enabling and disabling factors. This approach might be helpful for policymakers and social actors, seeking an answer to the perspectives of development of citizen-installed renewable energy capacities in Poland and other former Eastern Bloc countries.
An Novel Six-Segment Modulation Strategy for Three-Phase Isolated PFC Converter
Authors: Wang Huaibao , Wang Sheng , Ding Hao , Shi Changli , Jia Dongqiang , Chen Chao , Guerrero Josep M.
Published: April 2022

A three-phase isolated rectifier features bidirectional power conversion and galvanic isolation, and is attractive as a high-efficiency energy conversion system. However, when a conventional modulation is applied to this rectifier, the excessive DC-link current ripple will result in increasing switching losses or the size of DC-link inductance, which is not cost-effective. In order to effectively reduce the current ripple, this paper proposes a “six segment” PWM (Pulse Width Modulation) strategy. It can significantly reduce the current ripple compared with the existing “eight segment” PWM strategy. Meanwhile, the current quality of the grid is improved. Finally, the experimental tests were carried out. The experimental results reveal that, compared to the traditional “eight segment” PWM, the dc-side current ripple significantly reduced from 2 A to 0.8 A, the total harmonic distortion significantly reduced from 5.69% to 2.41%, and the power factor increased from 0.87 to 0.99, verifying the effectiveness of the proposed method.
Social Disconnectedness and Career Advancement Impact on Performance: The Role of Employees’ Satisfaction in the Energy Sector
Authors: Al-Haidan Saeed A. , Azazz Alaa M. S. , Elshaer Ibrahim A.
Published: April 2022

Employee performance in remote areas is a source of concern for the Saudi Arabian energy sector, which serves as the primary engine of the country’s economy. This research paper aimed to study the impact of social disconnectedness and career advancement on employees’ performance through employee satisfaction as a mediator. The targeted population was employees worked in remote areas in the energy sector. Data were collected using a web-based questionnaire and distributed electronically using social media. A total of 390 respondents participated in this study, and structural equation modeling (SEM) was employed to analyze the collected data. The study findings revealed that career advancement positively impacts employee performance; however, social disconnectedness negatively impacts employees’ performance. Both career and social factors had an indirect effect on employees’ performance through employee satisfaction. Lastly, results demonstrated a positive impact of employee satisfaction on employee performance. Important insights into theoretical and practical implications were discussed.
High Solid and Low Cellulase Enzymatic Hydrolysis of Cardoon Stems Pretreated by Acidified γ-Valerolactone/Water Solution
Authors: Fabbrizi Giacomo , Giannoni Tommaso , Lorenzi Leonardo , Nicolini Andrea , Iodice Paola , Coccia Valentina , Cavalaglio Gianluca , Gelosia Mattia
Published: April 2022

Lignocellulosic biomass is a nonedible matrix that can be efficiently exploited as feedstock in an integrated biorefinery after a proper pretreatment. An organosolv pretreatment using an acidified γ-valerolactone (GVL)/water solution was proposed to improve the cellulose enrichment and enzymatic saccharification of cardoon (Cynara cardunculus L.) stems. At the optimal pretreatment condition (140 °C, 0.6 GVL/water, and 2.24% H2SO4), xylan was efficiently removed from the cardoon, and up to 50% of its content was recovered in the aqueous fraction, while 86% of the cellulose was retained in the solid fraction. The resulting cardoon pulp showed a cellulose content of 91.5% and an enzymatic digestibility of 100%. An overall glucose production of 37.17 g/100 g raw material (90% theoretical maximum) was obtained using high solid loading (20% w/w) and a high enzyme dosage (60 FPU/g cellulose). At a low enzyme dosage, glucose concentrations of 169 g/L and 210 g/L were achieved using 10 FPU/g cellulose and 20 FPU/g cellulose, respectively. Therefore, an organosolv pretreatment can be an effective process for producing cellulose-enriched pulp with enhanced enzymatic digestibility from cardoon stems, providing a promising option for green lignocellulosic biorefineries that aim to produce high concentrations of glucose with low cellulase addition.
A Model of Risk Information Disclosures in Non-Financial Corporate Reports of Socially Responsible Energy Companies in Poland
Authors: Szczepankiewicz Elżbieta Izabela , Loopesko Windham Eugene , Ullah Farid
Published: April 2022

Risk management is critical for corporate finance management systems, in addition to corporate social responsibility (CSR) and sustainable development (SD) programs. Stakeholders need risk information to make informed judgments as to their involvement. No studies exist to date concerning disclosure of non-financial and financial risks in corporate annual statements and Polish strategic sector company reports. The authors sought to determine whether energy companies disclosed risks in non-financial annual reports in 2011–2020 (e.g., CSR, integrated, and board activity reports), and whether one can assess threats, including business activity risks and SD, based on these reports. We assessed the reports of all large Polish energy companies on a three- and five-degree scale to develop a model for risk information disclosures. We have three key empirical findings. Only half the analysed companies disclose annual financial data, threats, and risks. Less than half have implemented and operate enterprise risk management systems. The current ‘soft’ regulatory solutions give energy companies appreciable risk disclosure options, which often is counterproductive. We suggest developing a single integrated European Union (EU) regulation (e.g., directives, standards, or official principles) for non-financial risk disclosures. Our model classifies Polish energy company risks to business activity operations and risk management systems. Other sectors can use this universal model. Our results constitute progress in identifying company risks and may encourage continuing studies of other energy companies, especially in Central and Eastern Europe (CEE), which should be intensively developed. Research should also occur in other strategic sectors.
Exploring Wind Speed for Energy Considerations in Eastern Jerusalem-Palestine Using Machine-Learning Algorithms
Authors: Salah Saeed , Alsamamra Husain R. , Shoqeir Jawad H.
Published: April 2022

Wind energy is one of the fastest growing sources of energy worldwide. This is clear from the high volume of wind power applications that have been increased in recent years. However, the uncertain nature of wind speed induces several challenges towards the development of efficient applications that require a deep analysis of wind speed data and an accurate wind energy potential at a site. Therefore, wind speed forecasting plays a crucial rule in reducing this uncertainty and improving application efficiency. In this paper, we experimented with several forecasting models coming from both machine-learning and deep-learning paradigms to predict wind speed in a metrological wind station located in East Jerusalem, Palestine. The wind speed data were obtained, modelled, and forecasted using six machine-learning techniques, namely Multiple Linear Regression (MLR), lasso regression, ridge regression, Support Vector Regression (SVR), random forest, and deep Artificial Neural Network (ANN). Five variables were considered to develop the wind speed prediction models: timestamp, hourly wind speed, pressure, temperature, and direction. The performance of the models was evaluated using four statistical error measures: Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R2). The experimental results demonstrated that the random forest followed by the LSMT-RNN outperformed the other techniques in terms of wind speed prediction accuracy for the study site.
Wind Farms and Humidity
Authors: Adkins Kevin A. , Sescu Adrian
Published: April 2022

Several investigations have shown that enhanced mixing brought about by wind turbines alters near-surface meteorological conditions within and downstream of a wind farm. When scalar meteorological parameters have been considered, the focus has most often centered on temperature changes. A subset of these works has also considered humidity to various extents. These limited investigations are complemented by just a few studies dedicated to analyzing humidity changes. With onshore wind turbines often sited in agricultural areas, any changes to the microclimate surrounding a turbine can impact plant health and the length of the growing season; any changes to the environment around an offshore wind farm can change cloud and fog formation and dissipation, among other impacts. This article provides a review of observational field campaigns and numerical investigations examining changes to humidity within wind turbine array boundary layers. Across the range of empirical observations and numerical simulations, changes to humidity were observed in stably stratified conditions. In addition to the role of atmospheric stability, this review reveals that the nature of the change depends on the upstream moisture profile; robustness of the mixing; turbine array layout; distance from the turbine, in all three directions; and vertical temperature profile.
Power Electronics Converters for the Internet of Energy: A Review
Authors: Granata Samuele , Di Benedetto Marco , Terlizzi Cristina , Leuzzi Riccardo , Bifaretti Stefano , Zanchetta Pericle
Published: April 2022

This paper presents a comprehensive review of multi-port power electronics converters used for application in AC, DC, or hybrid distribution systems in an Internet of Energy scenario. In particular, multi-port solid-state transformer (SST) topologies have been addressed and classified according to their isolation capabilities and their conversion stages configurations. Non-conventional configurations have been considered. A comparison of the most relevant features and design specifications between popular topologies has been provided through a comprehensive and effective table. Potential benefits of SSTs in distribution applications have been highlighted even with reference to a network active nodes usage. This review also highlights standards and technical regulations in force for connecting SSTs to the electrical distribution system. Finally, two case studies of multi-port topologies have been presented and discussed. The first one is an isolated multi-port bidirectional dual active bridge DC-DC converter useful in fast-charging applications. The second case of study deals with a three-port AC-AC multi-level power converter in H-Bridge configuration able to replicate a network active node and capable of routing and controlling energy under different operating conditions.
Environmental Valorization of Rice Waste as Adsorbent Material for the Removal of Nitrates from Water
Authors: Mazzoccoli Michela , Arato Elisabetta , Moliner Cristina
Published: April 2022

An innovative water-treatment process consisting in reducing the nitrate concentration by using an active silica filter obtained from ashes produced during rice-straw thermal treatment has been developed by the LIFE LIBERNITRATE project. A life-cycle assessment (LCA) was carried out to evaluate the environmental impacts of this innovative process, from the production of ashes and extraction and activation of silica to the water treatment. These results were compared to the environmental impact derived from the use of bottled water, instead of tap water, where traditional water treatments (i.e., reverse osmosis) may not be available due to the high installation and operating costs. The comparison showed that the proposed innovative process could contribute to reducing the environmental impact in almost all analyzed impact categories (from 20% for photochemical oxidation to 90% for abiotic depletion) with respect to the use of bottled water. In addition, if conveniently optimized (for example reducing the amount of active silica used per day), the innovative process could further reduce the ecological footprint and be more eco-friendly than the use of bottled water and could be applied to treating water in small towns where reverse osmosis may not be installed. The LCA proved that the innovative process could contribute to reducing the environmental impact of water-treatment technologies resulting in lower environmental indicators with respect to the use of bottled water.
Wave Energy in the Pacific Island Countries: A New Integrative Conceptual Framework for Potential Challenges in Harnessing Wave Energy
Authors: Borges Posterari Jessica , Waseda Takuji
Published: April 2022

The Central and South Pacific have significant wave energy resources distributed through the region that are currently not being explored. Even though the wave energy resource in the Pacific has been studied, there is limited knowledge on the potential obstacles when inserting this new energy source into a unique and unexplored environment. Pacific Island countries (PICs) have distinctive characteristics that can become barriers to this technology, especially considering that local coastal and marine systems are fundamental for subsistence and local development. Thus, the success of a project relies on local acceptance. The current study developed an integrative conceptual framework for the PICs (ICFPICs) that derived from the integration of the elements of a political, economic, social, technological, environmental and legal (PESTEL) structured approach and further combined with a strengths, weaknesses, opportunities and threats (SWOT) approach to create a matrix that included relevant internal and external factors influencing a project. Four islands were analyzed through the ICFPICs to demonstrate the varying characteristics and challenges in the Pacific environment; the islands were Tubuai (French Polynesia), Viti Levu (Fiji), Rarotonga (Cook Islands), and ‘Eua (Tonga). Applying the ICFPICs to each island shows that Tubuai has significant technological issues, Rarotonga has mostly economic issues, Viti Levu is the most developed island but also has several potential issues in the social sphere, while ‘Eua has the fewest issues and is a viable candidate for further analysis. The ICFPICs can be used by decision makers, project developers, and stakeholders to recognize probable barriers when bringing wave energy technologies to the PICs and make informed decisions during the pre-feasibility stage.