Multiple Private Research Articles

The Impact of Intrinsic and Extrinsic Job Satisfaction on Turnover Intentions: A Moderating Effect of Public and Private Sector Employees

The operational efficiency in China's private and public sectors presents significant differences that managers are unaware of, leading to increased turnover intentions. The current research covers the impacts of intrinsic and extrinsic job satisfaction on turnover intentions within the Chinese public sector. This research investigates the correlation between job satisfaction and employee turnover intentions in the Chinese public and private sectors. Data were gathered via questionnaires distributed to employees from multiple public and private enterprises and institutions. The findings indicate clear differences between employees in the public and private sectors regarding the influence of job satisfaction on intentions to turnover. Specifically, Chinese public employees show less extrinsic job satisfaction and less desire to quit than employees employed in the private sector. Moreover, compared to employees in the private sector, those working in the public sector have a direct but insignificant negative relationship between extrinsic job satisfaction and turnover intentions. To improve employee motivation, it is recommended that public-sector managers prioritize enhancing extrinsic job factors and consider reallocating dissatisfied employees to more suitable roles. Furthermore, managers should evaluate whether their organization’s turnover rate is overly high, as it will deteriorate productivity and efficiency.

Analysis of Different Modality of Data to Diagnose Parkinson's Disease Using Machine Learning and Deep Learning Approaches: A Review

ABSTRACTThe dynamic nature of Parkinson's disease (PD) is that it gradually impacts regions of the brain that are responsible for the production of the dopamine hormone. Despite continuous efforts, no effective treatment or preventative approach exists for PD. Nonetheless, the disease can be detected. Our goal is to create a Machine Learning and Deep Learning‐based system that can detect Parkinson's disease from a variety of data sources with high accuracy, sensitivity, specificity and interpretability. However, there have been significant advancements in the field of research, especially the use of artificial intelligence in the Parkinson's disease diagnostic process. We reviewed articles that were released between 2018 and 2024, concentrating on the most current studies that had been published. We chose 70 research articles for our review paper based on a set of criteria from a variety of online databases, including IEEExpress, medical databases like PubMed, Google Scholar, ResearchGate and ScienceDirect, and various publishers, including Elsevier, Taylor & Francis, Springer, MDPI, Plos One and so forth. According to our review, the majority of works make use of voice data. Our review study found that the highest accuracy level of most papers was above 90%, and the most commonly used algorithms were CNN and SVM. The main goal of this review study is to look into and put together information about the different ways that artificial intelligence, especially Machine Learning, can be used to find Parkinson's disease. Using diverse data gathered from multiple public and private datasets, we can infer that the application of artificial intelligence, particularly Machine Learning algorithms, for identifying Parkinson's disease plays a crucial role in the medical field.

How he saw: Jerome Kagan's contexts of discovery.

Jerome Kagan was a psychologist and pioneer of developmental psychology, but he was intrigued by the natural sciences and read widely across history, biography, poetry, philosophy, cross-cultural anthropology, and the humanities. Drawing on unpublished archival and other primary source material, this essay describes two of Kagan's seminal studies in child development to demonstrate how their "contexts" facilitated scientific discovery and Kagan's own development as a researcher. A subset of Kagan's archival papers-including grant materials, correspondence, personal notes, and clipped articles-are also discussed to showcase the personal and scholastic material that Kagan read, wrote, and annotated, and which further advanced his scientific thinking. Collectively, these materials reveal the multiple contexts, both applied and private, in which Kagan "saw," thereby guiding his interdisciplinary approach to the scientific study of child development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Open source platform for Estonian speech transcription

AbstractThis paper presents our progress in developing and maintaining a public speech and speaker recognition platform for the Estonian language. The platform consists of a speech processing pipeline and a web-based user interface for end-users, offering transcript post-editing functionality. It is offered for free as a public service and is in active use. The service provides significantly higher speech recognition accuracy than commercial alternatives. We discuss the switch to a workflow management system and how it has improved the core speech processing pipeline. The core systems behind the platform have been made available as open-source code and deployed internally by multiple public and private institutions.

Risk Factors Associated with Bell's Palsy in Faisalabad: A Retrospective Study

Background: Bell's palsy is a common neurological disorder characterized by sudden facial paralysis, leading to significant distress and reduced quality of life. Despite extensive research, the exact etiology remains unclear, with various factors such as age, gender, and comorbid conditions like hypertension and diabetes implicated.Objective: This study aimed to identify the risk factors associated with Bell's palsy in a specific population, focusing on demographic and clinical variables.Methods: A retrospective study was conducted on 98 patients diagnosed with Bell's palsy in Faisalabad, Pakistan. Data were collected from multiple healthcare settings, including government and private hospitals, polyclinics, and independent medical practitioners. Variables such as age, gender, BMI, comorbidities, and history of exposure to cold were analyzed. Statistical analysis was performed using SPSS version 25.Results: Of the 98 patients, 56.12% were female, and 43.88% were male. The right side of the face was affected in 67.3% of patients, while 32.7% had left-side involvement. Significant associations were found between Bell's palsy and hypertension (p < 0.05), diabetes mellitus (p < 0.05), and exposure to cold (p < 0.05).Conclusion: Bell's palsy was more prevalent in females and younger individuals. Hypertension, diabetes, and cold exposure were identified as significant risk factors. These findings contribute to understanding the potential causes and risk factors for Bell's palsy, informing clinical management and prevention strategies.

Identification of tumor rejection antigens and the immunologic landscape of medulloblastoma

BackgroundThe current standard of care treatments for medulloblastoma are insufficient as these do not take tumor heterogeneity into account. Newer, safer, patient-specific treatment approaches are required to treat high-risk medulloblastoma patients who are not cured by the standard therapies. Immunotherapy is a promising treatment modality that could be key to improving survival and avoiding morbidity. For an effective immune response, appropriate tumor antigens must be targeted. While medulloblastoma patients with subgroup-specific genetic substitutions have been previously reported, the immunogenicity of these genetic alterations remains unknown. The aim of this study is to identify potential tumor rejection antigens for the development of antigen-directed cellular therapies for medulloblastoma.MethodsWe developed a cancer immunogenomics pipeline and performed a comprehensive analysis of medulloblastoma subgroup-specific transcription profiles (n = 170, 18 WNT, 46 SHH, 41 Group 3, and 65 Group 4 patient tumors) available through International Cancer Genome Consortium (ICGC) and European Genome-Phenome Archive (EGA). We performed in silico antigen prediction across a broad array of antigen classes including neoantigens, tumor-associated antigens (TAAs), and fusion proteins. Furthermore, we evaluated the antigen processing and presentation pathway in tumor cells and the immune infiltrating cell landscape using the latest computational deconvolution methods.ResultsMedulloblastoma patients were found to express multiple private and shared immunogenic antigens. The proportion of predicted TAAs was higher than neoantigens and gene fusions for all molecular subgroups, except for sonic hedgehog (SHH), which had a higher neoantigen burden. Importantly, cancer-testis antigens, as well as previously unappreciated neurodevelopmental antigens, were found to be expressed by most patients across all medulloblastoma subgroups. Despite being immunologically cold, medulloblastoma subgroups were found to have distinct immune cell gene signatures.ConclusionsUsing a custom antigen prediction pipeline, we identified potential tumor rejection antigens with important implications for the development of immunotherapy for medulloblastoma.

Cross-Modal Federated Human Activity Recognition.

Federated human activity recognition (FHAR) has attracted much attention due to its great potential in privacy protection. Existing FHAR methods can collaboratively learn a global activity recognition model based on unimodal or multimodal data distributed on different local clients. However, it is still questionable whether existing methods can work well in a more common scenario where local data are from different modalities, e.g., some local clients may provide motion signals while others can only provide visual data. In this article, we study a new problem of cross-modal federated human activity recognition (CM-FHAR), which is conducive to promote the large-scale use of the HAR model on more local devices. CM-FHAR has at least three dedicated challenges: 1) distributive common cross-modal feature learning, 2) modality-dependent discriminate feature learning, 3) modality imbalance issue. To address these challenges, we propose a modality-collaborative activity recognition network (MCARN), which can comprehensively learn a global activity classifier shared across all clients and multiple modality-dependent private activity classifiers. To produce modality-agnostic and modality-specific features, we learn an altruistic encoder and an egocentric encoder under the constraint of a separation loss and an adversarial modality discriminator collaboratively learned in hyper-sphere. To address the modality imbalance issue, we propose an angular margin adjustment scheme to improve the modality discriminator on modality-imbalanced data by enhancing the intra-modality compactness of the dominant modality and increase the inter-modality discrepancy. Moreover, we propose a relation-aware global-local calibration mechanism to constrain class-level pairwise relationships for the parameters of the private classifier. Finally, through decentralized optimization with alternative steps of adversarial local updating and modality-aware global aggregation, the proposed MCARN obtains state-of-the-art performance on both modality-balanced and modality-imbalanced data.

Federated learning implementation based on DDS data distribution service

Federated learning allows multiple local private clients to collaborate on training the same model without sharing each client's private data. It can achieve collaborative training between users while protecting data privacy and security. Therefore, it is advocated for use in the fields of Internet of Things, Internet of Vehicles, etc. There are security issues in the transmission process of federated learning models. How to ensure data privacy during local data collection, local model parameter transmission, model aggregation and performance testing while maximizing the use of private data is a question that people have been exploring. This paper proposes a DDS-based FL framework (FL-DDS) to achieve secure transmission of model parameters. The client and server are used as nodes in the DDS security domain, and the DDS data distribution mechanism is used to transmit model parameters. Through the DDS topic-based publish-subscribe mechanism, the global model and local model are transmitted through the DDS topic. At the same time, the DDS authentication component, access control component and encryption component are used to achieve domain-level security and intra-domain security of model transmission. Experiments show that (FL-DDS) can protect the privacy of model parameters without affecting communication performance.

Dynamics of a discrete-time mixed oligopoly Cournot-type model with three time delays

This paper analyzes a discrete-time Cournot competition model with time delays taking into consideration the dynamics of market interactions involving one public firm and multiple private firms. The model assumes that the production output of the public firm is influenced by the past output levels of the private firms. The output levels of the private firms are affected by the past production outputs of both the public firm and their private competitors. The study identifies two equilibrium states within the nonlinear system: a positive equilibrium and a boundary equilibrium. Through a stability analysis, it is established that the boundary equilibrium is a saddle point. In the absence of time delays, the stability region for the positive equilibrium is determined. The research explores various specific delay scenarios, finding conditions under which the positive equilibrium is asymptotic stability. Additionally, the occurrence of flip and Neimark–Sacker bifurcations are examined. In order to illustrate the complex dynamics, the paper provides a series of numerical examples.

Prevalence and Correlates of Psychiatric Symptoms Among Medical Students in Punjab: A Comprehensive Cross-Sectional Study

Background: Pain is evident, pressure, hopelessness and anxiety-is equally well-known to students with each passing academic semester in medical school. To understand the frequency and reasons of mental symptoms in MBBS students, the current study aims at investigating the level of MBBS students at several medical colleges in Punjab, Pakistan. Objective: To compare the results of stress, depressive, and anxious symptoms of several numbers of medical students studying in different medical colleges in Punjab and secondly, to evaluate the role of several demographics on these mental health indicators. Methods: The cross-sectional survey was completed between September 2023 to May 2024 with 350 medical students from multiple private and government medical colleges in Punjab. A cross-sectional survey was carried out including the Depression Anxiety Stress Scale-21 (DASS-21) as the research tool and the data aspires to be statistically analyzed. Results: the results indicated that the percentage of the medical students who reported to be stressed, sad, or anxious was 47.3%, 55.7%, and 61.4%, respectively. Female students also claimed higher levels of depression compared to male students 58.3% vs. 50. 1%, (p ≤0.01) and higher levels of anxiety 65.2% vs. 55.1%, (p ≤0.03). Students in rural locations reported greater levels of stress (52.6% vs. 43.2%, p ≤0.04) than urban ones. Conclusion: The study linked high levels of mental symptoms among medical students in Punjab to characteristics such as being a female student or originating from a rural area. The current study emphasizes the necessity of targeted programs and activities in the areas of mental health promotion and preventive measures among medical college students.

The penal Responsibility of the special moral Person on the Economic Crimes

The recent economic، social and technological developments resulted in the emergence of multiple private large economic and financial institutions or corporations (the "Corporations") that perform a range of activities with significant influence on the society. Indeed، this can bring great benefits to the society if their activities are properly made، while cause severe damage if they corrupt. Hence، the dangers caused by these corporations and the expanding scale of their damage can lead to economic crime، which is far greater than the harm caused by natural persons. Thus، it is no longer acceptable to ignore such crimes، particularly when the civil penalty is no longer appropriate to ignore their deviations on these corporations which brought huge profits to them. This created an advanced jurisprudence calling for the necessity of bringing punitive measures against these corporations in order to prevent and lessen their dangers to the society. The rapid transition from socialism to capitalism in Iraq after 2003 led to a sharp increase in the number and diversified activities and economic openness that controlled the economy، while the criminal jurisprudence was steps behind such fundamental changes. This research aims to demonstrate the importance of designating criminal responsibilities to these corporations to protect the society، and to identify the legal loopholes in Iraq on how to address them. Despite the existence of the principle of “publicity” for economic crimes or not economic crimes، according to the conditions that must be met in order to be take responsibility، under Article (80) of the Penal Code No. 111 of 1969، hitherto this article alone cannot go side-by-side with the dangers created by these corporations، which requires exclusive fundamental amendments، introducing more legislation providing strict punitive measures against these corporations aiming to safeguard the overall economic system.

Ethnic identity as a challenge to antidiscrimination law: protection, positionality and liminality

ABSTRACT Constitutions and antidiscrimination provisions tend to compartmentalise and operationalise ethnicity through religion, ethnic origin or country of origin, nationality, language and race. The growing focus on religion and race contributes to the entrenchment of ethnicity in religion and race, and this is not always fruitful. This article argues that antidiscrimination law should explicitly and robustly integrate ethnic identity as a protected (personal) characteristic in domestic law, independent of any other descriptors that may be recognised, and independent of existing group-based protections. Furthermore, this article argues that anti-discrimination infrastructure needs a provision of positionality and liminality. The concept of positionality facilitates the recognition of power dynamics present in the ascription of otherness, as well as the potential incongruences between identity ascription and actual self-identification. The concept of liminality enables the consideration of fluid and more flexible forms of self-identification across multiple public and private spaces.

Cloud storage cost: a taxonomy and survey

Cloud service providers offer application providers with virtually infinite storage and computing resources, while providing cost-efficiency and various other quality of service (QoS) properties through a storage-as-a-service (StaaS) approach. Organizations also use multi-cloud or hybrid solutions by combining multiple public and/or private cloud service providers to avoid vendor lock-in, achieve high availability and performance, and optimise cost. Indeed cost is one of the important factors for organizations while adopting cloud storage; however, cloud storage providers offer complex pricing policies, including the actual storage cost and the cost related to additional services (e.g., network usage cost). In this article, we provide a detailed taxonomy of cloud storage cost and a taxonomy of other QoS elements, such as network performance, availability, and reliability. We also discuss various cost trade-offs, including storage and computation, storage and cache, and storage and network. Finally, we provide a cost comparison across different storage providers under different contexts and a set of user scenarios to demonstrate the complexity of cost structure and discuss existing literature for cloud storage selection and cost optimization. We aim that the work presented in this article will provide decision-makers and researchers focusing on cloud storage selection for data placement, cost modelling, and cost optimization with a better understanding and insights regarding the elements contributing to the storage cost and this complex problem domain.

The Development of Agrotechnopark Model Based on Modern Villages

Agrotechnopark is an area for implementing various types of technology in agriculture, animal husbandry, fisheries, and product processing (postharvest), which has been reviewed by multiple governments and private research institutions and functions as a training ground and center for technology transfer to the broader community. Implementing the Agricultural Technology Park (TTP) uses socio-cultural, ecological, and economic approaches. A comprehensive understanding of community needs will be obtained through a socio-cultural system, which will become input for the company. At the same time, the environmental system will identify the potential basis of local resource excellence as a reference for community development activities. Furthermore, the economic approach is developing productive business units to increase people's income while paying attention to market demand. South Konawe Regency is one of the autonomous regions in Southeast Sulawesi, which is supported by its potential resources. The position of the South Konawe Regency area is very strategic, a southern cross-section of the Southeast Sulawesi peninsula that connects several Regencies/Cities in Southeast Sulawesi with prototypes of coastal and inland villages. One is Atari Jaya Village because it has a heterogeneous population composition, and most of the Javanese Transmigration community is reasonably competent in agricultural development. Because of this, socio-culturally and economically, this village grows and develops and is dynamic by carrying out the diffusion of technology in various fields supporting Agrotechnopark, such as the development of Integrated Farming (Multiple cropping) and integrated farming (Mixed culture) of plantation crops and plantations. Atari Jaya Village is also a central area for the development of Agropolitan both food crops, as well as plantation and horticultural crops on a national scale and a People's Plantation Centre worthy of being an Agricultural Technology Park Area (Agro et al.) in South Konawe Regency, Southeast Sulawesi Province. Development of the Agricultural Technology Park Area (TTP) to become a center for Agribusiness and Agro-fruit tourism as a basic framework for community and regional economic growth towards Konsel Hebat Regency. Atari Jaya Village was realized as an independent village, a pilot Agrotechnopark village in South Konawe Regency, and a service center for upstream and downstream Agribusiness trade in Agrofruit and plantations.

Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education

Abstract We estimate the equilibrium effects of a public school grant program administered through school councils in Pakistani villages with multiple public and private schools and clearly defined catchment boundaries. The program was randomized at the village level, allowing us to estimate its causal impact on the market. Four years after the start of the program, test scores were 0.2 standard deviations higher in public schools. We find evidence of an education multiplier: test scores in private schools were also 0.2 standard deviations higher in treated markets. Consistent with standard models of product differentiation, the education multiplier is greater for those private schools that faced a greater threat to their market power. Accounting for private sector responses increases the program’s cost-effectiveness by 85% and affects how a policy maker would target spending. Given that markets with several public and private schools are now pervasive in low- and middle-income countries, prudent policy requires us to account for private sector responses to public policy, both in policies’ design and evaluation.

Pharmacy faculty experiences with student academic entitlement: a multinational study from the Arab world

Academic Entitlement (AE) is the expectation by students to receive high grades or preferential treatment without significant effort. Exploring AE from faculty perspective has not been investigated in Arab colleges of pharmacy. The aim of this study was to explore experiences and perceptions towards student AE among pharmacy faculty in the Arab World. A cross-sectional, self-administered, anonymous, electronic survey was sent to pharmacy faculty across pharmacy colleges in Arab countries. The survey collected demographic data, an AE measure including 17 items reflecting seven AE components, and faculty perceptions and perceived reasons for AE. A total of 345 responses were collected. The AE level was moderate (46.05 ±7.29), and the highest scores among its components were for customer service expectation (62%) and responsibility avoidance (59%). In multiple linear regression, AE showed positive significant association with faculty in clinical pharmacy departments and those having fewer years of experience. Most common complaints heard by faculty from students were requests to turn in assignments late (90%), while the most common communication issues faculty faced with students were unprofessional verbal communication (58%) and unprofessional messages on social media (57%). Poor admission criteria (40%) and existence of multiple private colleges of pharmacy (37%) were the most common perceived reasons for AE by participating faculty. This study reveals moderate AE experienced by pharmacy faculty in the Arab World, as well as common complaints, communication issues, and AE reasons. In collaboration with other stakeholders, faculty play an important role in indicating expectations from students regarding AE, and research is warranted to check if such interventions reduce AE among pharmacy students.

What Is the Incidence of Anesthesia-Related Adverse Events in Oral and Maxillofacial Surgery Offices? A Review of 61,237 Sedation Cases From a Large Private Practice Consortium

BackgroundThe safety of the anesthesia team model performed in oral and maxillofacial surgery (OMS) offices has been criticized by professional and mainstream media. PurposeThis study aims to assess the incidence of adverse anesthetic events (AE) associated with the OMS anesthesia team model and identify risk factors associated with AEs. Study design, setting, sampleThis was a retrospective cohort study utilizing a patient database from Paradigm Oral Health®, Lincoln, Nebraska, a managed service organization (MSO). Subjects included were 14 and older, undergoing open-airway intravenous anesthesia for ambulatory OMS procedures using the OMS anesthesia team model at multiple private practices in the MSO network between June 30th, 2010, and September 30th, 2022. Exclusion criteria included patients younger than 14 or patients with incomplete medical records. Predictor variablePrimary predictor variables were age, sex, American Society of Anesthesiologists physical status classification system (ASA) score, type of surgical procedure performed, and the types of medications administered during sedation. Main outcome variableThe presence of an AE. The definition of an AE was modeled on the World Society of Intravenous Anesthesia (SIVA) definition. All AEs were identified through surrogate markers which were identified through chart review. One example of an AE is ventricular fibrillation, which necessitates application of medications, here the medication is the surrogate marker. CovariatesNone. AnalysesThe data were analyzed using t-tests and χ2 tests. P values ≤.05 were considered statistically significant. ResultsIncluded in the study were 61,237 sedation cases (53.87% female and 46.13% male), for 56,076 unique patients ranging from 14 to 98 years of age (mean 33.26 ± 18.35). An AE incidence of 3 per 100,000 per year (25 total events) was observed. Neither age, sex, ASA score, nor type of surgical procedure exhibited statistically significant associations with AEs. A statistically significant association was found between AEs and fentanyl (P = 0.0008). Conclusions and RelevanceThis investigation shows a smaller incidence of AEs than previous studies of the OMS anesthesia team model.

Streamlining neuroradiology workflow with AI for improved cerebrovascular structure monitoring

Radiological imaging to examine intracranial blood vessels is critical for preoperative planning and postoperative follow-up. Automated segmentation of cerebrovascular anatomy from Time-Of-Flight Magnetic Resonance Angiography (TOF-MRA) can provide radiologists with a more detailed and precise view of these vessels. This paper introduces a domain generalized artificial intelligence (AI) solution for volumetric monitoring of cerebrovascular structures from multi-center MRAs. Our approach utilizes a multi-task deep convolutional neural network (CNN) with a topology-aware loss function to learn voxel-wise segmentation of the cerebrovascular tree. We use Decorrelation Loss to achieve domain regularization for the encoder network and auxiliary tasks to provide additional regularization and enable the encoder to learn higher-level intermediate representations for improved performance. We compare our method to six state-of-the-art 3D vessel segmentation methods using retrospective TOF-MRA datasets from multiple private and public data sources scanned at six hospitals, with and without vascular pathologies. The proposed model achieved the best scores in all the qualitative performance measures. Furthermore, we have developed an AI-assisted Graphical User Interface (GUI) based on our research to assist radiologists in their daily work and establish a more efficient work process that saves time.

Local Community Detection in Multiple Private Networks

Individuals are often involved in multiple online social networks. Considering that owners of these networks are unwilling to share their networks, some global algorithms combine information from multiple networks to detect all communities in multiple networks without sharing their edges. When data owners are only interested in the community containing a given node, it is unnecessary and computationally expensive for multiple networks to interact with each other to mine all communities. Moreover, data owners who are specifically looking for a community typically prefer to provide less data than the global algorithms require. Therefore, we propose the Local Collaborative Community Detection problem (LCCD). It exploits information from multiple networks to jointly detect the local community containing a given node without directly sharing edges between networks. To address the LCCD problem, we present a method developed from M method, called colM, to detect the local community in multiple networks. This method adopts secure multiparty computation protocols to protect each network’s private information. Our experiments were conducted on real-world and synthetic datasets. Experimental results show that colM method could effectively identify community structures and outperform comparison algorithms.

The cost of transparency: Balancing acoustic, financial, and sustainability considerations for glazed office partitions

Substantial areas of modern offices may be glazed, including office partitions and doors. The desire for transparent connection between adjacent spaces may be driven by a need for natural lighting, the aesthetics of glass, and a desire for inclusivity and openness within organizations. At the same time, organizations require speech privacy for confidential communications, a requirement that relies on good sound isolation performance from glazing and seals. This paper examines the cost of transparency for modern offices, with a focus on balancing the acoustic performance of glazed partitions with spatial planning, post-pandemic occupancy patterns, financial costs, and the carbon cost of extensive glazing. Drawing on recent work to address poor sound isolation in a building with multiple small private offices with glazed partitions onto open office areas, this paper examines the impact of low Noise Isolation Class (NIC) values between adjacent spaces, including voice privacy concerns, acoustic discomfort and enforced changes to occupancy patterns. The design of glazed partitions should address a range of privacy needs while balancing the benefits and costs of a “transparent” workplace in terms of acoustics, construction costs, and embodied carbon.