bluuebunny/crossref_metadata_2025 huggingface dataset:
From Robotics to Prosthetics: What Design and Engineering Can Do Better Together
Authors: Fossati Maria R. , Grioli Giorgio , Catalano Manuel G. , Bicchi Antonio
Published: March 2023

This paper discusses how the disciplines of Design and Engineering are jointly addressing disability and somehow affecting its very interpretation. The discussion focuses on high-tech prostheses, where robotic devices substitute human body parts. The application of robotic technologies to prosthetics has a relatively long history. Nevertheless, only in the last decade have we witnessed applications reach the market and become available for a large base of users who were offered prostheses with superior motor and sensory performance. The process of bringing ever more advanced technologies to fruition by prosthetic users is fully ongoing today, with some promising solutions coming from robotics (such as, e.g. AI techniques or soft robotics materials) to be transferred to human use. In this transfer process, technology alone is insufficient to warrant success, and the need for a close collaboration between the Engineering domain and the Design disciplines is apparent. We address this point with specific reference to a case study, i.e. the transformation of an innovative but by-now
established technology in the industrial robotics field (the “Pisa/IIT SoftHand”) into a prosthetic hand (the “SoftHand Pro”). Besides obvious technical considerations about size, connections, control, and so on, which can be addressed with a thorough technical revision of the design, what makes the profound difference between the two devices is that, as a prosthesis, the SoftHand is intended as a human body part, and not as an external tool. To reach its ultimate goals, the hand should become a part of the human user, with his body and mind. The empirical approach and tools of Designers afford the possibility to enrich the re-design process, considering the final user at the centre of the process, in a sort of renewed humanistic approach.
The paper reflects this multidisciplinary approach and is structured as follows: the first part describes a cultural framework for the use of high-technology upper limb prostheses. This culture is defined through two significant relations (Users & Society; Users & Device). Inputs come from desk research conducted in different fields, ranging from Social Psychology to Medicine and Rehabilitation area. In this scenario, it is possible to extract design insights applicable to the design brief. The introduction of a robotic prosthetic hand (SoftHand Pro) and a related, single-user case study follow. The aim here is also to illustrate a process where engineering innovations are facilitated by tools from the Design field in the attempt to make the whole process coherently centred on users. Involved are all aspects, from material technology to the covering and finishing of the prosthetic device. The resulting, final prototype of the SoftHand Pro is finally presented.
Representation Bias in Data: A Survey on Identification and Resolution Techniques
Authors: Shahbazi Nima , Lin Yin , Asudeh Abolfazl , Jagadish H. V.
Published: March 2023

Data-driven algorithms are only as good as the data they work with, while datasets, especially social data, often fail to represent minorities adequately. Representation Bias in data can happen due to various reasons, ranging from historical discrimination to selection and sampling biases in the data acquisition and preparation methods. Given that “bias in, bias out,” one cannot expect AI-based solutions to have equitable outcomes for societal applications, without addressing issues such as representation bias. While there has been extensive study of fairness in machine learning models, including several review papers, bias in the data has been less studied. This article reviews the literature on identifying and resolving representation bias as a feature of a dataset, independent of how consumed later. The scope of this survey is bounded to structured (tabular) and unstructured (e.g., image, text, graph) data. It presents taxonomies to categorize the studied techniques based on multiple design dimensions and provides a side-by-side comparison of their properties.

There is still a long way to fully address representation bias issues in data. The authors hope that this survey motivates researchers to approach these challenges in the future by observing existing work within their respective domains.
Proportionality on Spatial Data with Context
Authors: Fakas Georgios J. , Kalamatianos Georgios
Published: March 2023

More often than not, spatial objects are associated with some context, in the form of text, descriptive tags (e.g., points of interest, flickr photos), or linked entities in semantic graphs (e.g., Yago2, DBpedia). Hence, location-based retrieval should be extended to consider not only the locations but also the context of the objects, especially when the retrieved objects are too many and the query result is overwhelming. In this article, we study the problem of selecting a subset of the query result, which is the most representative. We argue that objects with similar context and nearby locations should proportionally be represented in the selection. Proportionality dictates the pairwise comparison of all retrieved objects and hence bears a high cost. We propose novel algorithms which greatly reduce the cost of proportional object selection in practice. In addition, we propose pre-processing, pruning, and approximate computation techniques that their combination reduces the computational cost of the algorithms even further. We theoretically analyze the approximation quality of our approaches. Extensive empirical studies on real datasets show that our algorithms are effective and efficient. A user evaluation verifies that proportional selection is more preferable than random selection and selection based on object diversification.
Dopant Selective Photoelectrochemical Etching of SiC
Authors: Whiteley Samuel , Sorensen Adam , Vajo John J. , Sfadia Roy , Ladd Thaddeus D. , Cui Shanying , Graetz Jason
Published: March 2023

Single crystalline 4H-SiC is a wide-gap semiconductor with optical properties that are poised to enable new applications in MEMS and quantum devices. A number of key hurdles remain with respect to the micro and nano-fabrication of SiC to prepare precise photonic structures with nanometer-scale precision. These challenges include development of a fast, scalable etching process for SiC capable of producing a sub-nanometer roughness semiconductor surface while simultaneously reducing the total thickness variation across a wafer. Our investigation into UV photoelectrochemical processing of SiC reveals high dopant-type selectivity and the advantage of multiple etch stops to reduce layer thickness variation. We demonstrate dopant-type selectivities >20:1 using a single step and a >100x reduction in surface variation by combining two etch stops. Moreover, the etch rate is fast (>4 μm h−1) and the etched surface is smooth (∼1 nm RMS). These results demonstrate a scalable path to the fabrication of precise nanoscale SiC structures and electronic devices that will enable the next generation of MEMS and photonic quantum devices.
Guar Gum Supported ZIF-8 as an Effective Catalyst for Electrochemical Sensing of Gallic Acid in Liquid Food Samples
Authors: Thenrajan Thatchanamoorthy , Anandhakumar Muthaiah , Gokana Mohana Rani , Chaudhary Vishal , Rajaram Rajendran , Venkateswara Raju Chikkili , Wilson Jeyaraj
Published: March 2023

Monitoring of food-based products is mandatory in recent days as a result of increasing health-related issues and to produce ready-to-eat foods. Generally, in the food industry, the antioxidant property of phenolic compounds is utilized to improvize human health. Gallic acid (GA) is a widely known and abundant phenolic acid found used in numerous foods because of its huge health benefits. So far, many methods have been developed for the detection of GA using diverse nanocomposites. Likewise in the view of providing a simple and inexpensive material, we propose a zeolitic imidazolate framework (ZIF-8) functionalized with guar gum (GG) towards GA sensing. Here, the composite is prepared in a very easy and time-efficient manner using biocompatible GG. The physiochemical properties confirm the material formation due to the electrostatic interaction between the zinc ion of ZIF-8 and GG’s hydroxyl or carboxyl groups. Morphological studies confirm the nanostructured rhombic dodecahedral ZIF-8 particles embellished on the surface of GG’s microlayers. Further, electrochemical studies reveal the composite excellent behaviuor towards the GA sensing with a wide linear range of 200 nM–2.5 mM and a detection limit (LOD) of 60 nM. In addition to this, the composite offers significant selectivity, and good stability of up to 84% for 100 cycles along with acceptable repeatability and reproducibility. Finally, the investigation of the practical utility of unspiked wine, grape juice and tea samples also profound the composite’s exceptional sensing with remarkable recovery. Considering all these results, the proposed ZIF-8@GG composite can be fit for the fabrication of sensor devices towards food product testing in industries.
Multi-feature Optimization of a Gas Sensor Array to Improve Component and Concentration Detection Performance of VOC Mixtures
Authors: Xu Linjie , Zhao Jian , Wang Yongguang , Hu Yan , Yao Longchao , Zheng Chenghang , Yang Jian , Gao Xiang
Published: March 2023

Many studies focus on feature extraction and selection of gas sensor arrays for gas identification. In this work, we intended to find a feature subset obtained by selecting the most important features for simultaneously improving component and concentration detection performance of a gas sensor array to three harmful VOCs (toluene, methanol, and ethanol) and their mixtures. First, 30 features were extracted from 6 sensors’ responses to form a multi-feature set. Then, two feature selection methods based on Wilks’ Λ-statistic and random forest were employed to obtain the best feature combination. Seven out of 30 features were finally selected to form the optimal feature set. The gas identification accuracy is 94.3%, and the concentration estimation error is 0.79 ppm (RMSE). Through feature selection, not only qualitative and quantitative analyses performance of VOCs mixtures are significantly improved, but also system complexity (6 to 4 sensors) and computation cost (by about 15%) are effectively reduced.
Endothelial-derived extracellular vesicles from obese/hypertensive adults increase factors associated with hypertrophy and fibrosis in cardiomyocytes
Authors: Fandl Hannah K. , Garcia Vinicius P. , Treuth John W. , Brewster Lillian M. , Greiner Jared J. , Davy Kevin P. , Stauffer Brian L. , Desouza Christopher A.
Published: March 2023

In the present study we determined the effect of endothelial microvesicles (EMVs) isolated from obese/hypertensive adults on mediators of cardiomyocyte hypertrophy [cardiac troponin T (cTnT), α-actinin, nuclear factor-kB (NF-kB)] and fibrosis [transforming growth factor (TGF-β), collagen1-α1] as well as endothelial nitric oxide synthase (eNOS) expression and NO production. EMVs from obese/hypertensive induced significantly higher expression of hypertrophic (cTnT, α-actinin, NF-kB) and fibrotic (TGF-β) proteins as well as significantly lower eNOS activation and NO production in cardiomyocytes than EMVs from normal weight/normotensive adults. EMVs are a potential mediating factor in the increased risk of cardiomyopathy and heart failure with obesity/hypertension.
Does arterial stiffness mediate or suppress the associations of blood pressure with cardiac structure and function in adolescents?
Authors: Agbaje Andrew O.
Published: March 2023

The present study demonstrates that the associations of blood pressure with cardiac function and structure in adolescents may be mediated or suppressed by arterial stiffness depending on the blood pressure phenotype: systolic or diastolic. Arterial stiffness may be considered as an intermediate pathway to attenuate the effect of increased blood pressure on altered cardiac structure and function in youth.
Estrogen contributes to the sex difference in the occurrence of senescence-related T cells during the development of visceral adipose tissue inflammation
Authors: Imano Natsumi , Shojima Kensaku , Tamaki Kayoko , Shinmura Ken
Published: March 2023

The accumulation pattern of adipose tissue differs between the sexes; however, it is unclear whether sex differences exist during the development of adipose tissue inflammation and whether estrogen plays a role. We demonstrated sex differences in immune cells’ subpopulation of visceral adipose tissue. The proinflammatory environment appeared earlier in males than in females. In addition, our results suggest that estrogen plays a role in visceral adipose tissue inflammation, particularly by regulating the appearance of senescence-related T cells.
Fractal dimension of pulmonary gas and blood distribution assessed by synchrotron K-edge subtraction imaging: effect of bronchoconstriction
Authors: Bayat Sam , Degrugilliers Loïc , Porra Liisa , Strengell Satu , Petak Ferenc , Habre Walid
Published: March 2023

Here, we used an energy-subtractive imaging technique to assess the fractal dimension (Df) of lung gas and blood distribution and the effect of acute bronchoconstriction. We found that Df of gas significantly decreases in bronchoconstriction. Conversely, Df of blood exhibits gravity-dependent changes only, and is not affected by acute bronchoconstriction. Our data show that the fractal dimension of lung gas detects the emergence of clustered rather than scattered loss of ventilatory units during bronchoconstriction.
Relationship between muscle venous blood oxygenation and near-infrared spectroscopy: quantitative analysis of the Hb and Mb contributions
Authors: Koirala Bhabuk , Concas Alessandro , Sun Yi , Gladden L. Bruce , Lai Nicola
Published: March 2023

Within the near-infrared spectroscopy (NIRS) signal, the contribution from hemoglobin is indistinguishable from that of myoglobin. A computation analysis indicates that a linear relationship between muscle venous oxygen content and NIRS signals does not necessarily indicate a negligible myoglobin contribution to the NIRS signal. A reduced oxygen delivery increases the myoglobin contribution to the NIRS signal. The integrative approach proposed is a powerful way to assist in interpreting the elements from which the NIRS signals are derived.
Methionine-Mediated Regulation of Intestinal Lipid Transportation Induced by High-Fat Diet in Rice Field Eel (Monopterus Albus)
Authors: Hu Yajun , Zhang Junzhi , Cai Minglang , Chu Wuying , Hu Yi
Published: March 2023

An eight-week feeding trial explored the mechanism that supplemented methionine (0 g/kg, 4 g/kg, 8 g/kg, and 12 g/kg) in a high-fat diet (120 g/kg fat) on intestinal lipid transportation and gut microbiota of M. Albus (initial weight

25.03
±
0.13

 g) based on the diet (60 g/kg fat), named as Con, HFD+M0, HFD+M4, HFD+M8, and HFD+M12, respectively. Compared with Con, gastric amylase, lipase, trypsin (

P
<
0.05

), and intestinal lipase, amylase, trypsin, Na+/K+ -Adenosinetriphosphatase, depth of gastric fovea, and the number of intestinal villus goblet cells of HFD+M0 were markedly declined (

P
<
0.05

), while intestinal high-density lipoprotein-cholesterol, very low-density lipoprotein-cholesterol and microsomal triglyceride transfer protein of HFD+M0 were markedly enhanced (

P
<
0.05

); compared with HFD+M0, gastric lipase, amylase, trypsin, and intestinal lipase, trypsin, Na+/K+ -Adenosinetriphosphatase, microsomal triglyceride transfer protein, very low-density lipoprotein-cholesterol, and apolipoprotein -A, the height of intestinal villus and the number of intestinal villus goblet cells of HFD+M8 were remarkably enhanced (

P
<
0.05

). Compared with Con, intestinal occ, cl12, cl15, zo-1, zo-2 of HFD + M0 were markedly down-regulated (P <0.05), while intestinal vldlr, npc1l1, cd36, fatp1, fatp2, fatp6, fatp7, apo, apoa, apob, apof, apoo, mct1, mct2, mct4, mct7, mct12, lpl, mttp, moat2, dgat2 of HFD M0 were remarkably upregulated (

P
<
0.05

); compared with HFD+M0, intestinal gcn2 and eif2α of HFD+M8 were remarkably downregulated (

P
<
0.05

), intestinal occ, cl12, cl15, zo-1, zo-2, hdlbp, ldlrap, vldlr, cd36, fatp1, fatp2, fatp6, apo, apoa, apob, apof, apoo, mct1, mct2, mct8, mct12, lpl, mttp, moat2, and dgat2 were remarkably upregulated (

P
<
0.05

). Compared with Con, the diversity of gut microbiota of HFD+M0 was significantly declined (

P
<
0.05

), while the diversity of gut microbiota in HFD+M8 was significantly higher than that in HFD+M0 (

P
<
0.05

). In conclusion, a high-fat methionine deficiency diet destroyed the intestinal barrier, reduced the capacity of intestinal digestion and absorption, and disrupted the balance of gut microbiota; supplemented methionine promoted the digestion and absorption of lipids, and also improved the balance of gut microbiota.
Short-Term Power Prediction of Wind Power Generation System Based on Logistic Chaos Atom Search Optimization BP Neural Network
Authors: Zhang Yihan , Li Peng , Li Huixuan , Zu Wenjing , Zhang Hongkai
Published: March 2023

Wind power generation is the major approach to wind energy utilization. However, due to the volatility, intermittent, and controllability of wind power, it is difficult to control and scheduling of wind power, which brings challenges to the grid-connected operation and dispatch of wind power. Therefore, accurate power prediction of the wind power generation system is worthy of in-depth study. And this paper proposes a wind power prediction model based on logistic chaos atom search optimization (LCASO) optimized back-propagation (BP) neural network, aiming to achieve accurate and efficient power prediction. Moreover, this work utilizes data preprocessing to obtain more precise prediction results and related prediction evaluation indexes to quantificationally compare the effect of the proposed one with other prediction models based on GA-BP neural network and PSO-BP neural network. In contrast with the BP neural network, GA-BP neural network, and PSO-BP neural network, the simulation tests verify the comprehensive prediction performance and wider applicability of LCASO-BP neural network-based power prediction model.
Localized Simple Multiple Kernel K‐Means Clustering with Matrix‐Induced Regularization
Authors: Qiu Jiaji , Xu Huiying , Zhu Xinzhong , Adjeisah Michael
Published: March 2023

Multikernel clustering achieves clustering of linearly inseparable data by applying a kernel method to samples in multiple views. A localized SimpleMKKM (LI‐SimpleMKKM) algorithm has recently been proposed to perform min‐max optimization in multikernel clustering where each instance is only required to be aligned with a certain proportion of the relatively close samples. The method has improved the reliability of clustering by focusing on the more closely paired samples and dropping the more distant ones. Although LI‐SimpleMKKM achieves remarkable success in a wide range of applications, the method keeps the sum of the kernel weights unchanged. Thus, it restricts kernel weights and does not consider the correlation between the kernel matrices, especially between paired instances. To overcome such limitations, we propose adding a matrix‐induced regularization to localized SimpleMKKM (LI‐SimpleMKKM‐MR). Our approach addresses the kernel weight restrictions with the regularization term and enhances the complementarity between base kernels. Thus, it does not limit kernel weights and fully considers the correlation between paired instances. Extensive experiments on several publicly available multikernel datasets show that our method performs better than its counterparts.
Study on the Lateral Dynamic Impedance of Pile Groups in Transversely Isotropic Soil Using Novak’s Plane Model
Authors: Liu Linchao , Yan Qifang
Published: March 2023

In order to consider the effect of anisotropy of soil around the pile on the lateral vibration of pile groups, the soil around the pile is regarded as a transversely isotropic medium, and a lateral dynamic interaction model of pile-pile in transversely isotropic soil is established. According to Novak’s plane assumption and wave propagation theory, the lateral vibration of transversely isotropic soil layer is solved by introducing potential function and using mathematical and physical means, and the attenuation function of lateral displacement of free field is given. The Dobry and Dazetas simplified solution of attenuation function is different from that of solution of plane model. The pile-pile horizontal dynamic interaction factor in transversely isotropic soil is obtained by using the initial parameter method and Krylov function. The horizontal dynamic impedance of pile groups is obtained by using the pile-pile superposition principle. The change rule of the lateral displacement attenuation function of transversely isotropic soil with frequency is related to the direction and frequency. The ratio

G

h
v

of the shear modulus in the lateral plane to the shear modulus in the vertical plane and the pile spacing

S
/
d

have a great impact on the lateral vibration of pile groups, and when the pile spacing is large, the curves of attenuation function varying with frequency fluctuate greatly. The ratio of elastic modulus of pile to vertical plane shear modulus of soil

E

p

/

G

v

has an effect on the lateral stiffness of pile groups, which is related to frequency, while the effect on dynamic damping is not affected by frequency. The difference of mechanical properties on different surfaces of soil around the pile has a great influence on the lateral vibration of pile groups in transversely isotropic soil, and the influence of the anisotropy on the attenuation function of the lateral displacement and the dynamic impedance cannot be ignored.
Neonicotinoid Analysis in Sunflower (Helianthus annuus) Honey Samples Collected around Tekirdag in Turkey
Authors: Ozdemir Nurullah , Muz Mustafa Necati
Published: March 2023

In recent years, the widespread use of neonicotinoids in agricultural areas has caused environmental pollution due to its lower toxicity to mammals. Honey bees, which are considered as biological indicators of environmental pollution, can carry these pollutants to the hives. Forager bees returning from sunflower crops that have been treated with neonicotinoids treated sunflower fields cause residue accumulation in the hives, which reason colony-level adverse effects. This study analyses neonicotinoid residues in sunflower (Helianthus annuus) honey sampled by beekeepers from Tekirdag province. Honey samples have been subjected to liquid-liquid extraction methods before liquid chromatography-mass spectrometry (LC-MS/MS). The method validation was carried out to fulfill all the necessary requirements of procedures SANCO/12571/2013. Accuracy was in the range of 93.63–108.56%, for recovery in the range of 63.04–103.19%, and for precision in the range 6.03–12.77%. Detection and quantification limits were determined according to the maximum residue limits of each analyte. No neonicotinoid residues were found above the maximum residue limit in the sunflower honey samples analysed.
Quality of Life in the Management of Home Parenteral Nutrition
Authors: Schönenberger Katja A. , Reber Emilie , Huwiler Valentina V. , Dürig Christa , Muri Raphaela , Leuenberger Michèle , Mühlebach Stefan , Stanga Zeno
Published: March 2023

Introduction: Home parenteral nutrition (HPN) is a rare but challenging therapy for patients with mostly severe underlying diseases. We aimed to investigate patient-reported health-related quality of life (QOL) of patients receiving HPN and its development over time in particular. Methods: We assessed QOL of HPN patients in a prospective multicenter observational study (SWISSHPN II study). We designed a questionnaire to record symptoms and negative impacts of HPN and completed the validated Optum® SF-36v2® Health Survey with the patients. Results: Seventy patients (50% women) on HPN were included. HPN commonly affected feelings of dependency (n = 49, 70%), traveling/leaving home (n = 37, 53%), attending cultural and social events (n = 25, 36%), and sleep (n = 22, 31%). Most frequently reported symptoms were diarrhea (n = 30, 43%), polyuria (n = 28, 40%), nausea/emesis (n = 27, 39%), dysgeusia (n = 23, 33%), and cramps (n = 20, 29%). At baseline, mean (standard deviation) SF-36v2® physical and mental health component summary scores (PCS and MCS) were 45 (20) and 57 (19), respectively, and there was a trend toward improvement in PCS over the study period, while MCS remained stable. Satisfaction with health care professionals involved in HPN care was high. Conclusion: QOL is a crucial and decisive aspect of HPN patient care. Symptoms related to the underlying disease and PN are frequent. Impaired social life and an ambivalent attitude toward the life-saving therapy are major concerns for these patients and should be addressed in their care.
A proposed approach to discover nearest users on social media networks based on users' profiles and preferences
Authors: Hammoodi Mahmood Shakir , Al-Azawei Ahmed
Published: March 2023

Social media sites (SMSs) become essential platforms used by people, customers, and companies for communication and marketing. Social media networks (SMNs) allow access to individuals who share their information and this, in turn, can lead to build users' profiles. Profiles can consist of a basic description of users' characteristics such as name, age, gender, education, marital status, email, phone number, and location. Preferences, on the other side, describe users' behavior on SMNs. Earlier literature defined a user's identity in different networks based on matching his/her name only. This research, however, proposes an integrated approach for discovering the nearest users by considering profiles and preferences. The proposed approach includes three key steps. First, users are grouped based on their preferences such as personal interests. Second, properties’ values of a user profile and preferences are integrated to identify the nearest users. Finally, the nearest users to a certain user are identified by measuring the boundary distance. The findings show that the proposed approach can effectively identify the nearest users. Comparing the performance of the proposed approach with the two highly adopted approaches that rely on either users' profiles or preferences suggests that the proposed approach in this research is less prone to error.
Advanced optimal GA-PID controller for BLDC motor
Authors: Dakheel Hashmia S. , Abdullah Zainab B. , Shneen Salam Waley
Published: March 2023

The brushless direct current (BLDC) motor is characterized by high torque, which made it widely used in many industrial applications. To improve the working performance of the BLDC motor, the addition of controllers such as proportional integral derivative (PID) is adopted. To obtain high-performance controllers, the design process is adopted to develop a suitable algorithm. The genetic algorithm (GA) was chosen to tune the PID controller and get suitable parameters for each of kp, ki and kd with self-tuning. The design process is based on BLDC motor control using the GA to tune the traditional PID controller. Simulations were carried out for three cases including the absence of controllers secondly, by using the traditional control unit and finally with the GA. The integral time absolute error (ITAE) type error control standard for BLDC motor control system was selected. After conducting the simulation, the results demonstrated the superiority of the GA over the traditional ones in terms of response speed, (stability, rise, and settling) time and percentage overshootas details will be mentioned the model in the subsequent paragraphs of the research, finally the simulation results indicate the development and improvement of BLDC motor operation and performance during real time.
Influence of natural clouds on the performance of solar cell systems in Iraq
Authors: Al-Kaoaz Hiba Nadhim Ameen , Al-Yozbaky Omar Sharaf Al-deen Yehya
Published: March 2023

Solar energy generated by photovoltaic (PV) technology can be supplied to standalone systems, as it combines efficiency and cost-effectiveness. However, this combination is achieved only after considering the effects of shading, which can significantly influence electrical output. The primary factor that influences the use of solar energy in electricity generation is irradiation. PV cells are significantly impacted by shading, where the output of the PV cell reduces in the presence of a shadow. In this study, the researchers have presented an experimental analysis of how shading affects two PV cells, using the series and parallel configurations. The experimental work is installed at the University of Mosul, Department of Electrical Engineering, Renewable Lab (Iraq). MATLAB was used to simulate, evaluate, and compared the results to understand the effects of shading on PV cell output. This research offers an analytical technique to determine the probable effects of Partial shadowing conditions on PV power generation. The results provide the effects of partial shadowing in an annual performance loss of ≥10–30%. The orientation of the PV panels' tilt angle has an impact on their output power. When the tilt angle deviates from its ideal value, the PV panel's output drops off substantially.
Machine learning techniques for accurate classification and detection of intrusions in computer network
Authors: Paricherla Mutyalaiah , Ritonga Mahyudin , Shinde Sandip R. , Chaudhari Smita M. , Linur Rahmat , Raghuvanshi Abhishek
Published: March 2023

An incursion into the computer network or system in issue occurs whenever there is an attempt made to circumvent the defences that are in place. Training and examination are the two basic components that make up the intrusion detection system (IDS) and each one may be analysed separately. During training, a number of distinct models are built, each of which is able to distinguish between normal and abnormal behaviours that are included within the dataset. This article proposes a combination of ant colony optimization (ACO) and the firefly approach for feature selection. The final outcome of giving careful thought to the selection of features will eventually result in greater accuracy of categorisation. When classifying various sorts of features, we make use of a wide variety of machine learning (ML) algorithms, including AdaBoost, gradient boost, and Bayesian network (BN), amongst others. The tests and assessments made use of data obtained from three distinct datasets, namely NSL-KDD, UNSW-NB15, and CICIDS 2017. The degree of performance of an individual may be broken down into its component parts, which include the F1 score, accuracy, precision, and recall. Gradient boost performs far better when it comes to recognising and classifying incursions.
Comparative analysis of grid-connected bifacial and standard mono-facial photovoltaic solar systems
Authors: Abdul Kahar Nor Hidayah , Azhan Nurul Hanis , Alhamrouni Ibrahim , Zulkifli Muhammad Nubli , Sutikno Tole , Jusoh Awang
Published: March 2023

This paper describes the design of a solar photovoltaic (PV) system using simulation of PVsyst software. This work involves the simulation of bifacial and mono-facial PV solar in a large-scale solar system. For a bifacial system, the yearly total energy to the grid is 1699.6 MWh, with an average of 4.57 kWh/kWp/day. For a mono-facial system, the total energy to the grid over the year is 1645.3 MWh, with an average of 4.05 kWh/kWp/day. The average collection losses obtained for bifacial and mono-facial modules were 0.33 kWh/kWp/day and 0.82 kWh/kWp/day, respectively, with system losses of 0.15 kWh/kWp/day (bifacial) and 0.18 kWh/kWp/day (mono-facial). The average performance ratio for bifacial and mono-facial was 0.904 and 0.801, respectively. The bifacial PV system was able to generate profit in terms of Return on investment (ROI), around 357%, and reach a breakeven around 7 years. The payback period for a mono-facial PV system was around 8.1 years, with an ROI of 290.4%. This work mainly focuses on a comparative analysis of bifacial and mono-facial photovoltaics, emphasizing the effectiveness and the implementation suitability of bifacial photovoltaics over mono-facial PV solar systems.
Optimized ANN-fuzzy MPPT controller for a stand-alone PV system under fast-changing atmospheric conditions
Authors: Hichem Louki , Amar Omeiri , Leila Merabet
Published: March 2023

Solar energy is one of the most promising renewable energy resources. Over the last few decades, photovoltaic (PV) systems have grown in popularity. Since the maximum power point (MPP) of a solar system changes with environmental circumstances, the maximum power point tracking (MPPT) technique is required to get the most power out of the solar system. Various MPPT techniques based on classical and artificial intelligence (AI) methodologies have been proposed in the literature so far. In this paper, we aim to provide a thorough comparative analysis of the most widely used MPPT algorithms based on AI. The MPPT techniques discussed are based on fuzzy logic (FL), artificial neural networks (ANN), and the suggested hybrid approach ANN-fuzzy. The designed MPPT controllers are evaluated in the same PV system, which consists of a PV module, a DC-DC boost converter, and a DC load, under the same weather profile. Using the MATLAB/Simulink simulation tool, the tracking accuracy, response time, overshoot, and steady-state ripple of each method are tested in different weather conditions. The simulation results show that the ANN-fuzzy proposed tactic outperforms both the FL and the ANN MPPT controllers in correctly and successfully tracking the maximum power under diverse atmospheric conditions.
Using machine learning approach towards successful crowdfunding prediction
Authors: Raflesia Sarifah Putri , Lestarini Dinda , Kurnia Rizka Dhini , Hardiyanti Dinna Yunika
Published: March 2023

Crowdfunding is a concept that emerged due to difficulties in raising funds for community business projects, social activities, micro-enterprises, and start-ups conventionally. Crowdfunding uses internet technology as a bridge between the donor and the recipient of funds so that it can reach a wider range of donors. This study aims to compare the performance of machine learning approaches in predicting crowdfunding campaign success. Three machine learning algorithms were employed to predict crowdfunding campaign success, namely logistic regression, random forest, and extreme gradient boosting (XGBoost). The dataset used in this study contains data about all projects posted on Kickstarter from January 2020 to September 2022. To improve the prediction model's performance, experiments using principal component analysis (PCA) feature reduction and log transformation were conducted. The results show that the implementation of log transformation on the dataset can increase the prediction model's performance. Meanwhile, XGBoost algorithm performs better than linear regression and random forest.
High Gain Interleaved Boost Converter for Fuel Cell Applications
Authors: Seyezhai R. , Anitha R. , Mahalakshmi S. , Bhavani M.
Published: March 2023

Fuel cell is one of the promising technologies for distributed generation. For designing high efficiency fuel cell power systems, a suitable DC-DC converter is required. Among the various topologies, interleaved converters using switched capacitor are considered as a better solution for fuel cell systems due to high conversion efficiency. The objective of the paper is to design and implement a high gain interleaved converter using switched capacitors for fuel cell systems. In the proposed interleaved converter, the front end inductors are magnetically cross-coupled to improve the electrical performance and reduce the weight and size. Also, switched capacitors are used to improve the voltage gain of the converter. The proposed converter has been performed. Simulation study of interleaved converter using switched capacitors interfaced with fuel cells has been studied using Matlab/Simulink. A prototype has been developed to verify the simulation results.
A Variable Speed Wind Generation System Based on Doubly Fed Induction Generator
Authors: Arindya Radita
Published: March 2023

Wind energy has become one of the most important and promising sources of renewable energy, which demands additional transmission capacity and better means of maintaining system reliability. The evolution of technology related to wind systems industry leaded to the development of a generation of variable speed wind turbines that present many advantages compared to the fixed speed wind turbines. These wind energy conversion systems are connected to the grid through Voltage Source Converters (VSC) to make variable speed operation possible. The studied system here is a variable speed wind generation system based on Doubly Fed Induction Generator (DFIG). The rotor side converter (RSC) usually provides active and reactive power control of the machine while the grid-side converter (GSC) keeps the voltage of the DC-link constant. The additional freedom of reactive power generation by the GSC is usually not used due to the fact that it is more preferable to do so using the RSC. However, within the available current capacity the GSC can be controlled to participate in reactive power generation in steady state as well as during low voltage periods. The GSC can supply the required reactive current very quickly while the RSC passes the current through the machine resulting in a delay. Both converters can be temporarily overloaded, so the DFIG is able to provide a considerable contribution to grid voltage support during short circuit periods. This report deals with the introduction of DFIG,AC/DC/AC converter control and finally the SIMULINK/MATLAB simulation for isolated Induction generator as well as for grid connected Doubly Fed Induction Generator and corresponding results and waveforms are displayed.
Management of Urban Parking Lot Energy Efficiency with the Application of Wind Turbine and LED lights
Authors: Yuksek Bekir Z , Dakeev Ulan
Published: March 2023

A study of a parking lot lighting of a large manufacturing company in Iowa was implemented to evaluate monthly energy consumption. Mercury light bulbs with 227W ratings on the light poles were replaced with low power energy efficient LEDs to increase the overall efficiency. Additionally, a small scale wind turbine was installed to supply power to experimental light poles. Migration from the current gas bulbs to the LED light results yielded about 60% energy savings, while capital gains due to the generation of wind energy returned about 80% savings per month which recovered initial investments on the assets. The environmental impact of this study cannot be neglected and it also provided opportunity for STEM education in colleges and wind energy awareness in the society in Iowa by showing benefits from current experiments. Details of the methods and analyses should be particularly useful to urban planners because they show how standard references on investment in automobile parking should be modified to include efficient energy management. The authors proposed new way to limit the cost of energy consumptions and environmental pollution on wildlife and human health. Research implications are discussed in terms of the impact of natural features in urban areas for reduction of green house gas emissions and promoting alternative energy sources.
Two Parameter Controller for a Single Machine Infinite Bus System
Authors: Narasimha Raja Ch. Varaha
Published: March 2023

This paper shows the application of two parameter  controller with internal-Model principle to a single machine- infinite bus system (SMIB), to achieve design specifications and disturbance rejection. In the two parameter model the feedback- compensator is used to achieve required transient response by pole placement and input compensator is used to achieve required steady state response. Finally this method concludes that the method is systematic, general and yields good results.
Health inequalities in cause-specific mortality in Costa Rica: a population-based cohort study
Authors: Fantin Romain , Delpierre Cyrille , Barboza-Solís Cristina
Published: March 2023

OBJECTIVE: To analyze health inequalities in cause-specific mortality in Costa Rica from 2010 to 2018, observing the main causes for inequality in the country. METHODS: The National Electoral Rolls were used to follow-up all Costa Rican adults aged 20 years or older from 2010 to 2018 (n = 2,739,733) in an ecological study. A parametric survival model based on the Gompertz distribution was performed and the event death was classified according to the ICD-10. RESULTS: After adjustment for urbanicity, the poorest districts had a higher mortality than the wealthier districts for most causes of death except neoplasms, mental and behavioral disorders, and diseases of the nervous system. Urban districts showed significantly higher mortality than mixed and rural districts after adjustment for wealth for most causes except mental and behavioral disorders, diseases of the nervous system, and diseases of the respiratory system. Differences according to wealth were more frequent in women than men, whereas differences according to urbanicity were more frequent in men than in women. CONCLUSIONS: The study’s findings were consistent, but not fully similar, to the international literature.
Growth Differentiation Factor 15 and Risk of Bleeding Events: The Atherosclerosis Risk in Communities Study
Authors: Mathews Lena , Hu Xiao , Ding Ning , Ishigami Junichi , Al Rifai Mahmoud , Hoogeveen Ron C. , Coresh Josef , Ballantyne Christie M. , Selvin Elizabeth , Matsushita Kunihiro
Published: March 2023

Background

GDF15 (growth differentiation factor 15) is a potent predictor of bleeding in people with cardiovascular disease. However, whether GDF15 is associated with bleeding in individuals without a history of cardiovascular disease is unknown.

Methods and Results

The study population was from the ARIC (Atherosclerosis Risk in Communities) study. We studied the association of GDF15 with hospitalized bleeding events among 9205 participants (1993–1995) without prior bleeding and cardiovascular disease (mean age 60 years, 57% women, 21% Black). Plasma levels of GDF15 were measured in relative fluorescence units using DNA‐based aptamer technology. Bleeding was ascertained using discharge codes. We examined hazard ratios (HRs) of incident bleeding using Cox models and risk prediction with the addition of GDF15 to clinical predictors of bleeding. There were 1328 hospitalizations with bleeding during a median follow‐up of 22.5 years. The majority (76.5%) were because of gastrointestinal bleeding. The absolute incidence rate of bleeding per 1000 person‐years was 11.64 in the highest quartile of GDF15 versus 5.22 in the lowest quartile. The highest versus lowest quartile of GDF15 demonstrated an adjusted HR of 2.00 (95% CI, 1.69–2.35) for total bleeding. The findings were consistent when we examined bleeding as the primary discharge diagnosis. The addition of GDF15 to clinical predictors of bleeding improved the C‐statistic by 0.006 (0.002–0.011) from 0.684 to 0.690,
P
=0.008.

Conclusions

Higher levels of GDF15 were associated with bleeding events and improved the risk prediction beyond clinical predictors in individuals without cardiovascular disease.
Dominance, Language Experience, and Increased Interaction Effects on the Development of Pragmatic Knowledge in Heritage Bilingual Children
Authors: Sánchez Liliana , Goldin Michele , Hur Esther , Jimenez Abril , López Otero Julio César , Thane Patrick , Austin Jennifer , Markovits Rojas Jennifer
Published: March 2023

We investigate whether dominance, language experience, and increased interaction have an effect on the development of heritage bilingual children’s knowledge of the discourse-pragmatic constraints guiding null and overt subjects. A group of child heritage bilinguals (n = 18, mean age = 5;5) and comparison groups of adults: Mexican Spanish monolinguals (n = 15), heritage bilinguals in the United States (n = 16), and English monolinguals in the United States (n = 16) completed a language background questionnaire, a portion of the Bilingual English-Spanish Assessment (BESA) in English and Spanish, a forced-choice task (FCT) in Spanish, and two acceptability judgment tasks (AJT s): one in English and one in Spanish. Results showed that heritage children and adults pattern similarly and differently from adult monolinguals. Increased interaction at home has a positive effect on accuracy in the pragmatic conditions that license null subjects in Spanish without affecting overt subject patterns in English, the dominant language.
From Wild Beast to Huntress: Animal Imagery, Beauty, and Seduction in the Song of Songs and Proverbs
Authors: Létourneau Anne
Published: March 2023

This article investigates the bestiary used to represent the dynamics of attraction and seduction in the Song of Songs and the book of Proverbs. It examines mainly the predatory imagery, focusing on the lions and leopards the female lover associates with, in Song 4:8, as well as the “hunting ground” terminology used to characterize some of the strange women’s behaviors in Prov. 6:26; 7:22–23. Following Arbel (2015) and Imray (2013), the article contends that the female lover of Song of Songs and the strange women are not so different. Through a close philological examination of the passages staging these women, it sets out to decompartmentalize our understanding of what is an appropriate—or threatening—display of feminine charms and seductive strategies in the Hebrew Bible. This exegetical inquiry also brings the super/non-human persona of these women into focus.
Archaeological Perspectives on Contacts between Cairo and Eastern Ethiopia in the 12th to 15th Centuries
Authors: Insoll Timothy
Published: March 2023

A sustained relationship between Cairo, Egypt more broadly, and eastern Ethiopia appears to have existed, particularly in the Ayyubid and Mamluk periods. In the general absence of historical sources, it is archaeology that provides primary insight into how and why this relationship was maintained, particularly over the twelfth to thirteenth centuries. This is considered through archaeological data from the trading entrepot of Harlaa with particular reference to coins, glass wares, ceramics, bread/ textile stamps, marine shell, and jewellery moulds. The inferences that can be drawn from these regarding trade routes and markets are assessed. Finally, the Egyptian role in the decline of Harlaa and its replacement by Harar in the late fifteenth century are considered.
The Watermills of Mosul in the Ottoman Period
Authors: Usta Onur , Tonghini Cristina
Published: March 2023

This paper presents a documentary and archaeological study of the watermills in Ottoman Mosul to gain a political and social-economic understanding of the water-resource management in Mosul and its north-eastern hinterland in the early modern period. Watermills are of importance to historians, as the simple buildings equipped with sophisticated hydraulic devices, for teasing out various strands of water-resource management and agricultural economies from a regional and longue-dureé perspective. By synthesizing historical and archaeological methodological approaches, this paper aims to address the questions of what historical legacy of Mosul was left to the Ottoman Empire regarding the water infrastructure, including watermills and irrigation systems, and what contribution the Ottoman administration made to the development of Mosul’s water infrastructure. It presents an archaeological examination of a group of milling installations in Wadi Bandawai in the north of Mosul, demonstrating changes in settlement patterns during the long Islamic period, from the 7th to early 20th centuries, and also drawing attention to methodological problems with Islamic and Ottoman archaeology concerning the periodization of material culture.