bluuebunny/crossref_metadata_2025 huggingface dataset:
An investigation of low-density parity-check codes and polar codes for future communication systems
Authors: Mahdi Salih Layla , Mahmood Al-Qaradaghi Thuraya , Jamal Hamad Ameen Jalal
Published: January 2023

In the fifth-generation (5G) era and future, mobile internet and internet of things (IoT) are the driving forces for mobile communications’ development. The three main 5G usage scenarios: enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communications (URLLC), require improvement in throughput, reliability, and latency as compared with the previous fourth generation (4G) system. In this paper, an investigation is done on the coding part of the wireless communication systems. Two channel coding types; low-density parity-check (LDPC) code which is used as the coding scheme for data transmission, and Polar code which is utilized for control in 5G are discussed. Moreover, simulations are performed to assess their performance. The simulation results revealed the superiority of polar code for transmitting short information messages and LDPC for transmitting long data messages. The use of LDPC and polar codes in 5G communication systems is justified by their ability to accommodate a wide range of data lengths and code rates, as well as their good bit error rate (BER) performance. Furthermore, the effect of the number of iterations on the BER performance of LDPC code and different decoding algorithms of polar code are considered.
Cost-effective anonymous data sharing with forward security using improved authentication
Authors: Handore Shubhangi , Kolapkar Pallavi , Chavan Pratibha , Chavan Pramod
Published: January 2023

Cloud computing gives customers instant access to a network of remote servers, networks, and data centres. Cloud computing makes data analysis helpful to society and individuals. Sharing data with many people causes efficiency, integrity, and privacy issues. Ring signatures may enable secure and anonymous data transfer. It anonymizes data verification for cloud-based analytics. Identity-based (ID) ring signatures are becoming popular alternatives to public key infrastructure (PKI)-based public-key encryption. PKI bottlenecks are certificate verification time and cost. ID-based ring signatures speed up certificate verification. We observed that encrypting ID-based ring signatures with a variation of SHA-384 and adding forward security considerably improves their security. Padding divides the input text into 512-byte blocks and adds the length as a 48-bit value to the hash in newer SHA versions. Signatures made before a user's secret key was compromised are legitimate. If a user's secret key is compromised, it's impossible to compel all data owners to re-verify their data, hence a large-scale data sharing system must contain this feature. We implement, secure, and prove our method's use. SHA-384 is safer for cloud-based anonymous data sharing.
An optimal model for classification of lung cancer using grey wolf optimizer and deep hybrid learning
Authors: Mothkur Rashmi , Budhihal Nagendrappa Veerappa
Published: January 2023

In recent years, metaheuristic methods have shown major advantages in the field of feature selection due to its comprehensibility and possible extensive search competence. However, the majority of evolutionary computation-based feature selection algorithms in use today are wrapper approaches, which are expensive to compute, particularly for extensive biomedical data. Developing an effective evaluation strategy is crucial for significant reduction of computational cost. The proposed framework extracts deep feature from ResNet-50 and VGG-16 based convolutional neural models with initial segmentation process based on marker-controlled watershed method. Next the feature reduction is a two-fold approach with principal component analysis applied to reduce the dimensionality of large feature space from convolutional neural network (CNN) models as first step. The second step is optimal feature subset selection using a swarm intelligence method referred as modified grey wolf optimization. Finally, the selected feature subset is fed to various machine learning classifiers. The experimental result reveals that the proposed algorithm outperforms the other state-of-the-art methods with classification accuracy of 96.56%, thus upholding the dependability of the approach.
An automatic alignment of the business process and business value models: a novel MDA method
Authors: Kharmoum Nassim , Retal Sara , El Bouchti Karim , Rhalem Wajih , Ziti Soumia
Published: January 2023

With the massive development of end-users requirements, the model alignment has become an essential stage in software engineering, especially in the model driven architecture (MDA) approach, to absorb the end-user’s need. The purpose is to facilitate the alignment of new models from existing ones. Our contribution in this paper is to deal with the MDA higher abstraction lever by focusing on the automatic alignment of the business value with the business process models for the information system (IS). For our case, the data-flow diagram (DFD) illustrates the business process model, and the E3value model illustrates the business value model. However, the ATLAS-transformation language (ATL) ensures automatic alignment. The main goal is to facilitate and accelerate IS implementation while enhancing its quality.
Features of growth of agricultural crops and factors negatively affecting their growth
Authors: Yessenova Moldir , Abdikerimova Gulzira , Sadirmekova Zhanna B. , Glazyrina Natalya , Adikanova Saltanat , Tanirbergenov Adilbek , Karipola Mukhamedrakhimov , Mukhamedrakhimova Galiya
Published: January 2023

This article is about methods of analyzing aerial images. Images from Planet.com for crops in North Kazakhstan owned by the Center for Cereal Production and Research. A.I. Barayev. The main goal of the research work is to develop and implement algorithms that allow identifying and distinguishing factors in aerial photographs that adversely affect the growth of plants during the growing season. Spectral brightness coefficient (SBC), normalized difference vegetation index (NDVI), textural features, clustering, and integral transformations are used to solve the problem. Particular attention has been paid to the development of software tools for selecting features that describe textural differences to divide texture regions into subregions. That is weeds, and pests in aerial images. The application of a set of textural features and orthogonal transformations to the analysis of experimental data is explored to identify regions of potentially correlated features in the future. The analysis of the received data made it possible to determine the characteristics of changes in the reflective capacity of agricultural plants and weeds in certain stages of the growing season. The obtained information is of great importance for confirming the observations from space remote from the aerial images.
Detection of harmful gases present in the environment
Authors: Rai Pratiksha , Hasan Saeed Syed
Published: January 2023

The electronic nose (e-nose) is demonstrated in this research for detecting and identifying several forms of hazardous gases. We describe an e-noses for detecting several gases, including butane, acetone, methane, and ethanol. For dimensionality reduction in 3D representation, data processing approaches are based on the partial least square (PLS) method. The suggested system can be utilised for sensor optimization since different sensors with varied operating temperatures can be tested in many devices to find the best array for a specific detection or application. The results reveal that, depending on the sensor array characteristics, varying success rates in classification can be attained when discriminating contaminants. The preceding criteria lead to a new search for a portable, dependable, low-cost, and most efficient gas sensor. The major purpose of this study is to create a gas sensor array that can detect and monitor toxic and poisonous gases in the environment, as well as warn against dangerous organic compounds. Our goal is to create a sensor system that can distinguish the most significant decontamination gases while also being highly responsive, precise, low-effort, and low-power demanding.
Smart building trend, role, and position: a systematic literature review
Authors: Saputra Prasetya Cahya , Ramadhan Arief
Published: January 2023

Property growth, especially in high-rise buildings in developed and developing countries, has experienced a significant increase. The increasingly expensive resources and the development of information technology encourage the growth of smart buildings in almost all countries, especially in developed and developing countries, and become a trend. The Internet of things (IoT) is the main driver in the development of smart buildings. Property businesses are competing to adopt and implement smart buildings on their properties. This is further strengthened by the development of smart cities in almost all cities around the world, one of the criteria is a smart community. The purpose of implementing smart buildings is to make property management effective and efficient. Using the systematic literature review, this paper will discuss what components must be met for a property called a smart building, then what is the role of smart buildings for an area or community, and how the current smart building trend will be in the future.
Development of electrocardiogram intelligent and wearable monitoring system-assisting in care
Authors: Alagarsamy Manjunathan , Mariyarose Jemin Vijayaselvan , Shanmugam Nithya Devi , Vedam Joseph Michael Jerard , Joseph Mary Dallfin Bruxella , Suriyan Kannadhasan
Published: January 2023

The primary factor contributing to the high mortality rate in our country is coronary heart disease, which affects almost 50% of people from rural regions. Internet of things (IoT) contributes effectively to the development of point of care (POC) gadgets that support the medical upkeep of an expanding agricultural population. An electrocardiogram test is crucial for analysing cardiac disorders. Therefore, we must develop a POC piece of hardware to assess the health of the heart in an affordable manner and to design it for the patients without interfering with their daily regular procedure in order to monitor the patient's coronary heart disease. As a result, we must design an uninterrupted workbench, which consists of three main integrated parts. The first is a mobile Bluetooth low energy device that has 5-lead electrocardiogram (ECG) surveillance equipment and the smallest form factor. The smart phone Android application that inherits, resolves, and maps the data sent from the ECG device comes next. The patient's information and report details are then compiled on a cloud server for the doctor's future attribution needs.
Ultra-low leakage static random access memory design
Authors: Anitha Didigam , Ahmad Mohd. Masood
Published: January 2023

An ultra-low leakage static random-access memory (SRAM) cell structure with 8 transistors is proposed in this paper. Compared to the 6T SRAM and other existing 8T SRAM cells, leakage power of the proposed cell in hold mode reduced significantly. The stability parameters of the proposed cell are calculated using butterfly method and also N-curve method. Proposed SRAM achieves better write margin with slightly less read margin than 6T SRAM. Proposed technique consumes 790 PW of power in hold mode, which is very less compared to other existing techniques. Therefore, the proposed cell is appropriate for hold mode applications. The simulations are carried out by using Cadence (Virtuoso Schematic and layout editor) tools with GPDK45-nm technology.
Design and memory optimization of hybrid gate diffusion input numerical controlled oscillator
Authors: Reddy Gujjula Ramana , Perumal Chitra , Kodali Prakash , Rajanna Bodapati Venkata
Published: January 2023

The numerically controlled oscillator (NCO) is one of the digital oscillator signal generators. It can generate the clocked, synchronous, discrete waveform, and generally sinusoidal. Often NCOs care utilized in the combinations of digital to analog converter (DAC) at the outputs for creating direct digital synthesizer (DDS). The network on chips (NOCs) are utilized in various communication systems that are fully digital or mixed signals such as synthesis of arbitrary wave, precise control for sonar systems or phased array radar, digital down/up converters, all the digital phase locked loops (PLLs) for cellular and personal communication system (PCS) base stations and drivers for acoustic or optical transmissions and multilevel phase shift keying/frequency shift keying (PSK/FSK) modulators or demodulators (modem). The basic architecture of NCO will be enhanced and improved with less hardware for facilitating complete system level support to various sorts of modulation with minimum FPGA resources. In this paper design and memory optimization of hybrid gate diffusion input (GDI) numerically controlled oscillator based on field programmable gate array (FPGA) is implemented. compared with NCO based 8-bit microchip, memory optimization of hybrid GDI numerically controlled oscillator based on FPGA gives effective outcome in terms of delay, metal-oxide-semiconductor field-effect transistors (MOSFET’s) and nodes.
Breast invasive ductal carcinoma diagnosis using machine learning models and Gabor filter method of histology images
Authors: Kadhim Rania R. , Kamil Mohammed Y.
Published: January 2023

Breast cancer is the most common type of cancer in women and the leading cause of death from a malignant growth in the world. Machine learning methods have been created to help with cancer detection accuracy. There are several methods for detecting cancer. Histopathological images are more accurate. In this study, we employed the Gabor filter to extract statistical features from invasive ductal carcinoma histopathology images. From the histopathological images, we chose 100, 200, 400, 1000, and 2000 at random. These statistical features were used to train several models to classify these images as malignant or benign, including the decision tree, quadratic discriminant analysis, extra randomized trees, gradient boosting, Gaussian process, Naive Bayes, nearest centroid, multilayer perceptron, and support vector machine. The models' accuracy, sensitivity, specificity, precision, and F1_score were examined. The models produced the highest results when there were 100 images and a wavenumber of 0.2. While as the number of images increased, the models' effectiveness reduced. The most obvious finding to emerge from this study is that we suggest using deep learning instead of machine learning models for large datasets.
Side channel power analysis resistance evaluation of masked adders on FPGA
Authors: Zhao Yilin , Nishikawa Hiroki , Kong Xiangbo , Tomiyama Hiroyuki
Published: January 2023

Since many internet of things (IoT) devices are threatened by side-channel attacks, security measures are essential for their safe use. However, there are a variety of IoT devices, so the accuracy required depends on the system’s application. In addition, security related to arithmetic operations has been attracting attention in recent years. Therefore, this paper presents an empirical experiment of masking for adders on field programmable gate arrays (FPGAs) and explores the trade-off between cost and security by varying the bit length of the mask. The experimental results show that masking improves power analysis attack resistance, and increasing the bit length of the random numbers used for masking increases security. In particular, the series-connected masked adder is found to be effective in improving power analysis attack resistance.
OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue
Authors: Chen Zhi , Liu Yuncong , Chen Lu , Zhu Su , Wu Mengyue , Yu Kai
Published: January 2023

This paper presents an ontology-aware pretrained language model (OPAL) for end-to-end task-oriented dialogue (TOD). Unlike chit-chat dialogue models, task-oriented dialogue models fulfill at least two task-specific modules: Dialogue state tracker (DST) and response generator (RG). The dialogue state consists of the domain-slot-value triples, which are regarded as the user’s constraints to search the domain-related databases. The large-scale task-oriented dialogue data with the annotated structured dialogue state usually are inaccessible. It prevents the development of the pretrained language model for the task-oriented dialogue. We propose a simple yet effective pretraining method to alleviate this problem, which consists of two pretraining phases. The first phase is to pretrain on large-scale contextual text data, where the structured information of the text is extracted by the information extracting tool. To bridge the gap between the pretraining method and downstream tasks, we design two pretraining tasks: ontology-like triple recovery and next-text generation, which simulates the DST and RG, respectively. The second phase is to fine-tune the pretrained model on the TOD data. The experimental results show that our proposed method achieves an exciting boost and obtains competitive performance even without any TOD data on CamRest676 and MultiWOZ benchmarks.
Locally Typical Sampling
Authors: Meister Clara , Pimentel Tiago , Wiher Gian , Cotterell Ryan
Published: January 2023

Today’s probabilistic language generators fall short when it comes to producing coherent and fluent text despite the fact that the underlying models perform well under standard metrics (e.g., perplexity). This discrepancy has puzzled the language generation community for the last few years. In this work, we posit that the abstraction of natural language generation as a discrete stochastic process—which allows for an information-theoretic analysis—can provide new insights into the behavior of probabilistic language generators, for example, why high-probability texts can be dull or repetitive. Humans use language as a means of communicating information, aiming to do so in a simultaneously efficient and error-minimizing manner; in fact, psycholinguistics research suggests humans choose each word in a string with this subconscious goal in mind. We formally define the set of strings that meet this criterion: Those for which each word has an information content close to the expected information content, namely, the conditional entropy of our model. We then propose a simple and efficient procedure for enforcing this criterion when generating from probabilistic models, which we call locally typical sampling. Automatic and human evaluations show that, in comparison to nucleus and top-k sampling, locally typical sampling offers competitive performance (in both abstractive summarization and story generation) in terms of quality while consistently reducing degenerate repetitions.
Variations in the Diurnal Cycle of Precipitation and Its Changes with Distance from Shore over Two Contrasting Regions as Observed by IMERG, ERA5, and Spaceborne Ku Radar
Authors: Hayden Lindsey J. M. , Tan Jackson , Bolvin David T. , Huffman George J.
Published: January 2023

The diurnal cycle of precipitation is highly regional and is typically a product of multiple competing, highly localized effects. The diurnal cycle in regions such as the Amazon and the Maritime Continent are of particular interest, due to the complex coastal and terrain effects. The high spatial and temporal resolution provided by the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) dataset are used in this study to examine the fine-scale features of the diurnal cycle in these regions. Using an 18-yr (2000–18) record of IMERG precipitation observations, diurnal and semidiurnal phase and amplitude are calculated using a fast Fourier transform (FFT) method on half-hourly averaged precipitation at 0.1° × 0.1°. Clear patterns of precipitation phase propagation with distance from shore are shown over both regions, with the diurnal phase and amplitude exhibiting a strong dependence on the distance from the coastline. Semidiurnal cycles are generally weaker than the diurnal cycle except in some isolated locations. Similar analysis is also conducted on the ERA5 reanalysis data in order to evaluate the model’s representation of the precipitation diurnal cycle. The model captures the broadscale patterns of diurnal variability but does not capture all the fine-scale patterns nor the exact timing that is observed by IMERG. Comparisons are also made to a long-record Ku radar dataset created by combining Tropical Rainfall Measuring Mission (TRMM) and GPM observations, thus providing an additional point of comparison for the timing of the ERA5 precipitation peak, since the timing precipitation can be different, even in between observational datasets.
The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study
Authors: Virtanen Jussi , Roine Antti , Kontunen Anton , Karjalainen Markus , Numminen Jura , Oksala Niku , Rautiainen Markus , Kivekäs Ilkka
Published: January 2023

Objective:

Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present.

Methods:

Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k-Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference.

Results:

A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k-nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%.

Conclusions:

The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air.
Fulfilling 6 Domains of Health Care Quality: A Qualitative Parental Caregiver Study of Pediatric Telehealth During a Pandemic
Authors: Aultman Julie , Bassi Mandip , Richner Gwendolyn , Delahanty Sarah , Rush Sarah , Spalding Steven , Grossoehme Daniel
Published: January 2023

Using qualitative methods, we examine telehealth care quality from the perspective of parents of pediatric patients during a pandemic. We fill a gap in the literature essential for measuring effectiveness of pediatric telehealth. A total of 22 participants (n = 21 female; n = 1 male) enrolled in 1 of 9 interviews and focus groups conducted in 2021. Transcribed data were thematically analyzed and organized based on the 6 domains of quality health care by the Institute of Medicine (IOM). Analyzed data revealed 7 themes and 52 codes. Pediatric telehealth visits were perceived as efficient, timely, safe, and generally effective by parents for their child’s health care. Participants experienced equal or greater time with their child’s care provider via telehealth than through in-person visits. Qualitative results directly align with IOM domains of quality health care and contribute to the growing literature and evidence that may lead to improved telehealth outcomes and better preparedness for emergent public health events.
Ampicillin and Gentamicin Treatment for Early Onset Neonatal Sepsis: When One Size Does Not Fit All
Authors: Daniels Kristin , Arrieta Antonio , Nieves Delma J. , Bhakta Kushal , Tran M. Tuan , Osborne Stephanie , Morphew Tricia
Published: January 2023

Based on in vitro susceptibilities and the concern for emergence of resistance and long-term safety, ampicillin plus gentamicin remains the recommended antibiotic regimen for early onset neonatal sepsis. Our objective was to identify potential limitations of this regimen based on clinical and pathogen characteristics while minimizing risks associated with prolonged antibiotic exposure. We identified 43 gram-negative pathogens in 42 patients. Escherichia coli ( E coli) occurred in 50% and Streptococcus agalactiae in 23.8% of patient. Ampicillin resistance was common, particularly in E coli (85.7%). Mortality was 23.8%, all due to E coli. We found that E coli is the most frequent pathogen and has a high mortality particularly in neonates < 1500 g; mortality is high with the current dosing strategy when E coli is resistant to ampicillin even when sensitive to gentamicin; resistance to gentamicin remains low but seems to be increasing while resistance to third-generation cephalosporins remains very low.
Evaluation of Nonconvulsive Status Epilepticus and Nonconvulsive Seizures in a Pediatric Intensive Care Unit
Authors: Cavusoglu Dilek , Olgac Dundar Nihal , Kamit Fulya , Anil Ayse Berna , Arican Pinar , Zengin Neslihan , Gencpinar Pinar
Published: January 2023

We aimed to identify nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) in a pediatric intensive care unit (PICU). A prospective cohort study on 35 patients who underwent continuous electroencephalographic monitoring in the PICU was done. The patients were evaluated to collect data of their demographics, clinical diagnoses, clinical seizures by electroencephalography, and neuroimaging findings. One case with NCSE and 4 cases with NCS were diagnosed among the 35 patients. The etiology of the patient with NCSE showed antiepileptic drug (AED) withdrawal. The etiology of the patients with NCS included electrical injury, head trauma, subarachnoid hemorrhage, and pneumonia. The findings suggest that younger age, epilepsy, acute structural brain abnormalities, abrupt cessation of AED, and clinically overt seizures before NCSE/NCS are associated with significant risk for NCS/NCSE. In addition, the electrical injury may also be considered as a risk factor for electrographic seizure though such a case has not yet been reported.
Minding (Your Own and) Others’ Business: Assigning Co-Responsibility in Cabinet Decisions
Authors: Shpaizman Ilana , Cavari Amnon
Published: January 2023

In coalition governments, parties invest much effort to manage delegation costs to individual ministers. In this article, we examine an intra-executive mechanism for managing delegation costs: Assigning ministerial co-responsibility in cabinet decisions. Using data of cabinet decisions in Israel, we test when and under what conditions co-responsibility is assigned. We find that co-responsibility is assigned strategically by cabinet members weighing the risk of a drift against the costs of imposing co-responsibility. These findings demonstrate an understudied mechanism through which coalition governments narrow ministerial autonomy and informational advantage once policies reach the cabinet. In doing so, this research contributes to a better understanding of policymaking in coalition governments.
Barriers to and ways of facilitating the implementation of Aragon’s Health-Promoting School network
Authors: Rodrigo-Sanjoaquín Javier , Murillo-Pardo Berta , Corral-Abós Ana , Lorente-Echeverría Silvia , Zaragoza Casterad Javier
Published: January 2023

Background:

The Health-Promoting School (HPS) framework offers a comprehensive approach to promoting health in schools. Aragon’s HPS network is a local organisation which has identified the need for closer cooperation between the education and health sectors as the main challenge facing its programme.

Objectives:

Previous studies from countries implementing HPS approaches have identified various outcomes and challenges. However, there is insufficient evidence to identify potential barriers to HPS implementation in Spain. This study therefore set out to explore these issues within the context of the HPS network in Aragon.

Method:

Three focus groups were held in different cities (Zaragoza, Huesca and Teruel) between April and May 2020. The total sample comprised 18 adults ( M = 45.21; SD = 12.61), 60% of whom were men. Eleven participants were HPS stakeholders (i.e. teachers, HPS coordinators) and seven were external collaborators (e.g. university professors, researchers).

Results:

The main barriers identified were the excessive workload for professionals involved in the network, limitations imposed by contextual factors such as lack of teacher and family involvement, and lack of supervision and communication within the HPS network. Strengthening collaboration with work in other settings, the provision of continuing education for teaching staff and more systematic evaluation were identified as potential ways forward.

Conclusion:

Using the principles identified in this paper, Aragon’s HPS network should be further developed to enhance effective implementation and improve sustainability.
Book review: Mahendra Prasad Singh, Federalism in India
Authors: Roy Himanshu
Published: January 2023

Mahendra Prasad Singh, Federalism in India. Delhi: SAGE, 2022, 294 pp., ₹1,295.
Book review: R. K. Mishra and Geeta Potaraju, Creating, Building and Sustaining an Institution
Authors: Raj Sridhar
Published: January 2023

R. K. Mishra and Geeta Potaraju, Creating, Building and Sustaining an Institution. New Delhi: Academic Foundation, 2022, 189 pp.
Working from Home and Worker Well-being: New Evidence from Germany
Authors: Yang Duanyi , Kelly Erin L. , Kubzansky Laura D. , Berkman Lisa
Published: January 2023

The COVID-19 pandemic piqued interest in remote work, but research yields mixed findings on the impact of working from home on workers’ well-being and job attitudes. The authors develop a conceptual distinction between working from home that occurs during regular work hours (replacement work-from-home) and working from home that occurs outside of those hours (extension work-from-home). Using linked establishment-employee survey data from Germany, the authors find that extension work-from-home is associated with lower psychological well-being, higher turnover intentions, and higher work-to-family and family-to-work conflicts. By contrast, replacement work-from-home is associated with better well-being and higher job satisfaction, but higher work-to-family conflict. Extension work-from-home has more negative effects for women’s well-being and work-to-family conflict. This distinction clarifies the conditions under which remote work can have positive consequences for workers and for organizations.
The influence of a Learning to Forgive Program on institutional offending and recidivism among offenders with mental disorder
Authors: Oduntan Emmanuel , Onasanya Oluwadara , Anderson Tara , DesRoches Andrea , Mondal Prosanta , Mela Mansfield
Published: January 2023

Previous researchers have demonstrated that learning to forgive may reduce the likelihood of offending/reoffending. Forgiveness therapy may be useful for rehabilitation by assisting traumatized individuals to release revengeful emotions. The current study is a follow up to a previous study that examined the effects of a 6-week forgiveness psychoeducational intervention for offenders with mental disorders. The aim of the current study was to determine any differences for participants who received a forgiveness intervention versus a control group for rates of recidivism (likelihood of reoffending and length of time to reoffend) and type of institutional offense. Recidivism data was collected through the Canadian Police Information Center. Both the control and treatment group in this study were selected from offenders with mental disorder at the Regional Psychiatric Centre, a multilevel forensic psychiatry hospital in Saskatoon, Canada. Results indicated that participants who received the forgiveness intervention took significantly longer than the control group to both commit non-violent offenses, and to be convicted of any offense. Results suggest that forgiveness therapy for offender populations may improve behavior and reduce recidivism.
Punk teacher education: Finding ways to interrupt the harmful effects of teacher accountabilities
Authors: Vass Greg
Published: January 2023

In recent years a suite of policies and practices that are strongly influenced by efforts to make the work of educators and education providers more accountable, have had a powerful impact across the sector in settings such as Australia. In part, this goes some way to explaining why many working in the teaching profession report being dissatisfied with their role in education, and significant numbers leave the profession within the initial 5 years in Australia. Both in this context and beyond, there is a growing chorus of voices that encourage finding ways to push back and interrupt the impacts of accountability initiatives in education. Teacher education is itself one of the contexts in which this contestation is playing out, and whether it be voiced in terms of reimagining, revolutionising, or reclaiming education, the core sentiment can be interpreted as a type of call to arms for those working with educators. In this paper, I will make the case that punk can productively contribute to efforts responding to the influences of dominant culture in education. Punk in this usage can be thought of as social practices that generate cultural resources that can be utilised to question and critique dominant culture.
‘Dare to be silent’: Re-conceptualising silence as a positive pedagogical approach in schools
Authors: Su Feng , Wood Margaret , Tribe Robert
Published: January 2023

In Western societies, school pedagogies tend to be biased in favour of talk and emphasise the links between talking, thinking and learning. Thus talk is often privileged over silence as the basis for learning activities in classrooms, sustained by theories of learning which afford priority to talk. Such cultural bias towards talk means that by contrast, silence can be perceived negatively and construed as a form of ‘non-participation’. Through a systematic literature review of journal articles relating to silence as a pedagogical approach published between 2000 and 2021, this article reappraises the role and value of silence in school education. Some of the apparent paradoxes of silence as a pedagogical approach, different types and uses of silence in the classroom, cultural dimensions of silence and the relationships between silence, power and critical pedagogy are examined. The pedagogical importance of silence as a participatory approach to learning emerges as a significant point for educators and the paper offers some suggestions for potential applications in classroom practice.
Complex disaster response framework to reduce urban disaster vulnerability
Authors: Choe Taeyoung , Kim Jiho , Shin Mincheol , Kim Kwangyoung , Kim Mucheol
Published: January 2023

Cities are vulnerable to a range of disasters that can occur simultaneously due to their complexity. Therefore, an effective disaster response plan is needed to reduce the disaster vulnerability of cities. In particular, evacuation route management is important for reducing the losses from a disaster. Efficient disaster response can be realized by searching for suitable evacuation routes and effective road network management. In this paper, we propose a disaster response framework based on a multilayered road network structure and evacuation routes based on our road network. The suggested road structure consists of three layers for the effective management of the network. An A* algorithm-based search for multiple evacuation routes under different conditions in response to an individual disaster on the configured road map provides a safe route for evacuees. As a result, the damage caused by disasters in urban areas can be ameliorated.
Exorcisms, extraction of unwanted entities, and other spiritual struggles around the body: A comparative perspective Exorcismes, extractions d’entités indésirées et autres combats spirituels autour du corps: une perspective comparative
Authors: Bindi Serena , Giménez Béliveau Verónica
Published: January 2023

Exorcism is a long-standing practice in the history of religions and has increased in contemporary societies. The introduction to the dossier ‘Exorcisms, extractions of unwanted identities, and other spiritual struggles around the body’ proposes a revision of the production of contemporary social sciences – in particular, anthropology and sociology – on exorcism. First, we propose a reflection on the category of exorcism, and then we discuss some of the issues that underlie research on the contemporary practice: ritual performance, the status of exorcism in modernity, the relationship with therapeutic and healing practices, the discussion of exorcism as a gendered ritual, and the political dimension of the practice.
Care commons: Infrastructural (re)compositions for life sustenance through yet against regimes of chronic crisis
Authors: Sanchez Isabel Gutierrez
Published: January 2023

Infrastructures constitute key sites in the contemporary crisis regime. Emerging infrastructural configurations, particularly in the urban setting, are raising questions about the possibilities and challenges that these transformations may bring regarding more just and sustainable modes of social provision. Attention is being drawn to the grassroots, where experiments with novel forms of organisation are bringing about new collective contexts and political conceptions. In this context, infrastructure has been proposed as a concept to both examine contemporary crises and devise ways to cope with breakdown that can gesture towards living alternatives at the service of life. In this article, I engage this debate through an ethnographic study of two grassroots initiatives in Athens (Greece) intervening in the realm of life sustenance. I will show that these people-driven initiatives (re)compose networked infrastructures in ways that advance organisational modes of social provision different to institutions, and forms of political engagement and possibility. They do so by infrastructuring care through commoning. I will argue that infrastructural systems of care commons contribute to an infrastructural imagination that moves away from modern ideals towards values of relationality, conductivity, care and repair, which may nurture a transformative politics for a world in crisis, yet against crisis regimes.
Varied presentations of congenital dengue infection in neonates
Authors: Bhatter Shivani , Jain Jenisha
Published: January 2023

Dengue fever is a common viral infection in the tropics and is prevalent in Southeast Asia. Dengue infection is associated with increased morbidity and mortality in the perinatal period. Transplacental transfer of dengue infection is rare. Here we report of four such cases.
Active After Sunset: The Politics of Judicial Retirements in India
Authors: Dam Shubhankar
Published: January 2023

Indian judges retire, but not into inactivity. Many pursue careers in government-appointed roles. Scaffolded around the concept of institutional corruption, this article interrogates the history, law and politics of the retirement careers of judges in India. Three questions take centre stage in this analysis: What types of careers do retired judges pursue? Why do they pursue them? How do judges’ post-retirement ambitions impact their pre-retirement decisions? The cumulative analysis suggests that the Supreme Court of India, not specific judges, benches or decisions, is institutionally corrupt. The system of post-retirement jobs cycles like an economy of influence that is weakening the institution’s effectiveness, especially its capacity for impartial adjudication in matters that involve governments. But the Indian court’s performance and its public reception also reveal unique attributes that can enrich our general understanding of institutional corruption and separate the concept’s essential features from its auxiliary ones.
Can a Protectionist Measure be Non-Discriminatory? Comparative Federal Markets and a Proposal for a Definition of Discrimination Under s 92 of the Australian Constitution
Authors: Nagy Csongor István
Published: January 2023

Three decades ago, in Cole v Whitfield, the High Court of Australia opted for a discrimination-based standard with the argument that s 92 of the Australian Constitution targets solely protectionist measures. This article demonstrates, with the use of comparative law analysis, that, in contrast with this teleology, the High Court has built a lacunose definition of discrimination that is incapable of covering the whole spectrum of protectionist measures. It argues that measures having an asymmetric impact should be considered discriminatory and countenanced only if they are justified by a local legitimate end and are proportionate, even if they rely on distinctions that are not based on out-of-state origin.
Ending the Transformation before the Goal is Fulfilled: The Case of Head Start
Authors: Shpaizman Ilana
Published: January 2023

To make a comprehensive policy change, actors often turn to the gradual path where they introduce small-scale changes hoping that their accumulation will meet their goal over time. Nonetheless, they often stop the transformative process before meeting their original goal. This paper argues that this can be explained by policy learning. When actors learn from reliable information that the accumulation of the small-scale changes does not meet their expectations, they stop the transformative process. At the same time, the policy is not illuminated due to feedback effects and beliefs by the majority of actors that the small-scale changes are beneficial.
Mini-publics, Social Legitimacy and Institutional Collaboration: Some Inherent Trade-offs and Three Alternative Design Strategies
Authors: Ravazzi Stefania
Published: January 2023

Over the last few decades, an increasing number of governments have promoted the setting up of so called “mini-publics” to integrate policymaking processes in an attempt to improve policy decisions. This phenomenon has highlighted the importance of mini-publics to become fully integrated in our democratic systems. By presenting the findings of empirical research conducted on 29 local mini-publics, this paper aims to explain how mini-public design elements can affect the capacity of mini-publics to trigger or hinder two key integration mechanisms: the social legitimation mechanism and the institutional collaboration mechanism.
Design of developed distributed observers for nonlinear time-delay systems
Authors: Ghotb Hajar , Ataei Mohammad , Siahi Mehdi , Moarefianpour Ali
Published: January 2023

This paper considers a distributed observer design for a class of nonlinear systems with time delays in a network. Specifically, each distributed observer has access to partial output as it communicates with its neighboring observers through consensus protocols defined on the network. The network includes N local observers where adjacent observers transmit and receive information through a delayed telecommunication graph network. The design method is based on Lipschitz condition of nonlinear terms while having time-delay cases in view. Appropriate selection of Lyapunov functions is made and the Jensen inequality applied in delayed nonlinear systems in undirected, strongly connected, and directed networks containing spanning trees. Also, via the design algorithm, the necessary and sufficient conditions for the design of parameters are defined so as to stabilize the error dynamics. Finally, numerical simulations are provided to verify the effectiveness of the proposed method.
Experimental investigation on effect of variations in tire pressure on control performance of ABS under µ-jump road conditions based on tire operating parameters
Authors: Köylü Hakan , Tural Ersin
Published: January 2023

The changes in tire pressure will cause braking force to significantly vary due to the change in the tire-to-road contact during hard braking. The most important reason of this issue is the changes in road contact because of the changes in the vertical stiffness and slip stiffness of tire, as tire pressure varies. Therefore, in this study, it was aimed to investigate the effects of the tire pressure on anti-lock brake system (ABS) control performance through vertical and slip stiffness of tire. For this, first, the friction coefficient extended to tire pressure was integrated into the braking dynamics equations using the magic tire model. In this way, the effects of tire pressure were analytically revealed on braking performance. Then, taking into account the theoretical results, ABS braking tests were carried out with three different tire pressures: higher (38 psi) and lower (25 psi) tire pressure than the nominal (33 psi) tire pressure. In experimental studies, tests were carried out for braking initial speeds 30 and 60 km/h with the same tire pressures in µ-jump road conditions. In this way, the effects of the tire pressure were experimentally investigated on control performance of ABS under critical road conditions. At 33 psi tire pressure, the highest brake pressure was observed when switching to wet roads. At 25 psi tire pressure, the brake pressure did not build up in time. This showed that low tire pressure causes brake pressure to increase with a delay. On the slippery part, the lock-up limit is closer at 38 psi tire pressure. Therefore, it was seen that the decrease and increase in tire pressure have great effect on control performance of ABS under µ-jump road conditions.
Tracking the trajectory of an object in a noisy environment with unknown statistics: A novel robust Kalman filter residue-based approach
Authors: Cheded Lahouari , Doraiswami Rajamani
Published: January 2023

A novel robust Kalman filter (KF)-based controller design approach is proposed to accurately track a specified trajectory under unknown stochastic disturbance, known deterministic disturbance, and measurement noise. The system is nonlinear and is approximated by a piecewise-linear dynamic model. The Box–Jenkins model is an augmented model of the signal and the disturbance, is non-controllable and observable, while the signal model is controllable and observable. An emulator-based two-stage identification is employed to obtain an accurate system model needed to design the robust controller. The system and its KF are identified, and the signal and output errors are estimated. From the identified models, the signal, its KF, the disturbance model, and the whitening filter are all obtained using balanced model reduction techniques. It is shown that the signal model is a transfer matrix description relating the system output and KF residual, and the residual is the whitened output error. The disturbance model is identified by inverse filtering. A new combined feedforward–feedback controller is designed and implemented using an internal model of the reference driven by both the error between the reference and the signal estimate, and by the feedforwarded reference signal. The proposed scheme was successfully evaluated on a simulated autonomously guided drone.