Miracle-dz/UniFAR-FTUs huggingface dataset:
Technology Ethics in Public Service: Envisioning the Role of the Techno-Ethicist

Abstract In terms of technological progress, students of public administration confront a challenging dilemma where normative reflection in the realm of technology ethics has not kept pace with the rapidity and magnitude of technological advancement. Consequently, this necessitates further reflection on how to best apply aspects of ethical behavior to the development and usage of technology in the public sector. The significant role of the technology ethics in public service has received meager consideration in the literature, lacking a theoretical foundation that can help guide practitioners (as techno-ethicists) through rapid transitions in technological progress. Using the philosophy of technology literature, this article seeks to address this gap in public administration theory by considering first, how technological advancements affect the nature of didactic power relationships between the public and government; and second how the concept of technological nonneutrality is framed as a basis for structuring what obligations public administrators have when adopting and using technology in public service. This includes reflection upon the expanding role of newer technologies such as Artificial Intelligence in reshaping the nature of government-society relationships. Framing techno-ethical principles in theoretical dialogue prompts greater awareness for how practitioners may effectively respond as moral agents to rapidly changing technological advancements.
Cost of Warning of Unseen Threats: Unintended Consequences of Connected Vehicle Alerts

One goal of the connected vehicle program is to raise the situation awareness of drivers to unseen events in the driving environment. Warnings of unseen threats may prompt a directed visual search for that threat at the expense of overlooking other intervening threats along the way. This study assessed the distraction potential of alerts to unseen threats. Twenty-two participants drove an instrumented vehicle on a closed course and encountered threat situations, such as a car entering the road from a side road obstructed from the driver's view. On each pass, there were two sandbags that served as secondary threats, and the driver was instructed to press a response button whenever one was detected. The control condition bags were placed at locations on the course where the driver was undistracted and encountered no primary threats. The threat bags were positioned so that they became visible shortly after the warning of a primary threat appeared on an in-vehicle display but before the primary threat became visible. The results showed that advance warnings improved primary threat detection time. That is, when drivers were given advance warning of the presence of an upcoming threat, the drivers identified the presence of the threat sooner than when no warning was given. Unfortunately, this facilitation came at a cost of reduced detection distance and reaction time to the secondary threats that were present in the roadway. Future research should investigate whether this effect persists for more critical secondary threats.
A Rolling Bearing Fault Diagnosis Approach Based on Multiscale Entropy

When the rolling bearing works in fault condition,the complexity of the vibration signal will change.Sample entropy(SE) is defined to measure the complexity of time series in single scale,while multiscale entropy(MSE) is used to measure the complexity of time series in different scales,which contains much more information.Based on this,a new rolling bearing fault diagnosis approach based on MSE and SVM was put forward.In this paper,the concepts of SE and MSE were introduced,then MSE was applied to extract the feature information from bearing vibration signals and SVM was used to identify the rolling bearing fault categories.Finally the proposed approach was applied to the experimental data,and the analysis results indicate that the proposed approach can fulfill the rolling bearing fault classification effectively.
Management of chemotherapy dose intensity for metastatic colorectal cancer

Chemotherapy dose intensity is a momentous parameter of antitumor clinical medication. In certain clinical trials, the actual application dose of the chemotherapeutic drugs is frequently different from the prescribed dose. The chemotherapy dose intensity completed in different trials is also variable, which has an impact on the treatment efficacy, disease prognosis and patient safety. When these agents are tested in the population, chemotherapy reduction and delay or failure to complete the planned cycle constantly occur due to age, performance status, adverse reactions and other reasons, resulting in the modification of the chemotherapy dose intensity. The present review analyzed the correlation between the chemotherapy dose intensity and the incidence of adverse reactions, the treatment efficacy and disease prognosis in clinical trials of metastatic colorectal cancer. Moreover, the clinical applications of chemotherapy dose intensity were discussed. Based on individual differences, the present review analyzed the clinical trials that examined the efficacy of the chemotherapy dose intensity in different patient populations. The conclusions suggested that different populations require a specific dose intensity to reduce treatment toxicity without affecting the curative effect.
Lu Tong Ke Li protects neurons from injury by regulating inflammation in rats with brain trauma

Abstract Currently, there is no effective therapy for traumatic brain injury (TBI). Therefore, this study was conducted to determine the protective effect of Lu Tong Ke Li (LTKL), a Chinese medicine, for TBI in experimental animals. The TBI rat model was induced using the modified Feeney's protocol. The rats were divided into four groups: Sham group, Control group, LTKL lower‐dose group (LTL, 2 g/kg/day, p.o.), and LTKL higher‐dose group (LTH, 4 g/kg/day, p.o.). The Neurological Severity Score (NSS) was used to examine neurological function. Magnetic resonance imaging was performed to check the brain tissue lesions in rats. Cell apoptosis in the damaged area was evaluated using the Terminal deoxynucleotidyl transferase deoxy‐UTP‐nick end labeling assay. Reverse‐transcription polymerase chain reaction was used to investigate the expression of inflammatory cytokines, including tumor necrosis factor‐α (TNF‐α), interleukin 1β (IL‐1β), and interleukin 10 (IL‐10). The TBI rat model was successfully constructed. Neurological function was enhanced at 14, 21, and 28 days post TBI in the LTH groups, indicated by gradually decreased NSS scores. Administration of LTH led to fewer brain defects in the damaged area, and the number of apoptosis cells in the brain injury area markedly decreased. LTKL treatment led to upregulation of IL‐10 expression and downregulation of TNF‐α and IL‐1β expressions at the molecular level. LTKL can improve the neurobehavior of TBI. The neuroprotective effect was probably related to regulation of inflammation cytokines. Our results provide crucial evidence of the potentially useful application of LTKL in the therapy of TBI in clinic practice in the future.
Design and Characteristics Analysis of a Novel Single-phase Hybrid SRM for Blender Application

In this paper, the design and characteristic analysis of a novel single-phase hybrid switched reluctance motor (HSRM) for the purpose of replacing the universal motor in commercial blenders are presented. The proposed motor is easy to manufacture due to its simple yet robust structure with minimized power switches and no torque dead-zone. Moreover, the proposed HSRM is able to deliver a high starting torque as a requirement for blending hard food or even ice. The stator has permanent magnets (PMs) mounted on its inner surface and the rotor has a wide pole arc and salient poles that contribute to its high starting torque profile and the elimination of the torque dead-zone. Finite element method (FEM) is used to analyze the characteristic of the proposed motor. Finally, the prototype is manufactured and its performance is verified through experiments.
Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items' Popularity

Visually-aware recommender systems (VRSs) integrate products’ image features with historical users’ feedback to enhance recommendation performance. Such models have shown to be very effective in different domains, ranging from fashion, food, to point-of-interest. However, test-time adversarial attack strategies have recently unveiled severe security issues on these recommender models. Indeed, adversaries can harm the integrity of recommenders by uploading item images with human-imperceptible adversarial perturbations capable of pushing a target item into higher recommendation positions. Given the importance of items’ popularity on the recommendation performance, in this work, we evaluate whether there is an influence of items’ popularity on the attacks’ effectiveness. To this end, we perform three state-of-the-art adversarial attacks against VBPR (a standard VRS) by varying the adversary knowledge (white-vs. black-box) and capability (the magnitude of the perturbation). The results obtained evaluating attacks on two real-world datasets shed light on the remarkable efficacy of the attacks against the least popular items’ when planning novel defenses.
Distributed Denial of Service attack

A distributed denial-of-service (DDoS) attack is an attack in which multiple compromised computer systems attack a target, such as a server, website or other network resource, and cause a denial of service for users of the targeted resource. The flood of incoming messages, connection requests or malformed packets to the target system forces it to slow down or even crash and shut down, thereby denying service to legitimate users or systems. Distributed Denial of Service Attacks have recently emerged as one of the most newsworthy, if not the greatest, weaknesses of the Internet. This paper attempts to explain how they work, why they are hard to combat today, and what will need to happen if they are to be brought under control. It is divided into four sections. The first is an overview of the current situation. The second is a detailed description of exactly how this attack works, and why it is hard to cope with today; of necessity it includes a description of how the Internet works today. The third section describes the short-term prospects, what can be done today to help alleviate this problem; and the final section describes the long-term picture, what will change to bring this class of problem under control, if not eliminate it entirely. And finally there are some appendices: a bibliography, giving references to original research work and announcements; a brief article on securing servers; and acknowledgements for the many people who helped make this paper possible.
Evolution of Therapeutic Patient Education: A Systematic Scoping Review and Scientometric Analysis

Therapeutic patient education (TPE) aims to empower the patients and their caregivers to effectively care for and manage their conditions. Such educational programs have been shown to improve health behaviors, disease outcomes, and quality of life among different patient populations. The field of TPE has evolved extensively over decades, owing to interdisciplinary research. No study so far has been done to map this field, to identify the stakeholders and gaps requiring future research. By leveraging the theory of co-citation, CiteSpace was used to visualize the bibliographic data pertaining to TPE research. A total of 54,533 articles published in English language were analyzed to identify influential funders, regions, and institutes contributing to this field. Besides these, significant theoretical and empirical contributions that shaped this field were mapped. Our analysis revealed several important insights. Most of the important theories that helped shape TPE were inspired from the social sciences. Five important research themes were identified: disorders, study designs utilized in TPE research, the scope of the TPE literature and outcomes, and populations. The research focused on improving perceptions, behaviors, and attitudes toward health promotion, reducing stigma, self-management and medication adherence. Most of the research was developed in the context of high-income countries. Future research should involve patients and use digital technology. Meta-analytical studies need to be done to identify the effectiveness and moderators of TPE interventions across different disorders. Further research should involve low and middle-income countries (LMIC) to ensure knowledge and technology transfer.
PHYTOCHEMICAL IN DIFFERENT TYPES OF POLLEN AND THEIR EFFECTS ON HONEY BEES

In this study, the phytochemical analysis was performed for four major types of pollen namely broad bean (Vicia faba), date palm (Phoenix dactylifera), Egyption clover (Trifolium alexandrinum) and maize (Zea mays) which were collected by honey bee colonies from the study area. Phytochemical analysis showed that clover pollen occupied the highest total antioxidant capacity (TAC), flavonoid and tannins 6480.67, 7155.63 and 752.21 mg/100gm, respectively, comparead with the other pollen types, while the highest percentage of phenol was found in date palm pollens 734.13 mg/100gm. To determine the nutritional effects on some criteria such as food consumption rate, brood rearing, bee population, stored pollen and longevity of honey bee four types of pollen were supplied to honey bee colonies. Fifth group was fed on mixture from all pollen types at a rate of 25% of each type, whereas the sixth group was free from pollen and used as control. The highest food consumption was from date palm pollen, followed by broad bean, clover and maize. Concerning brood rearing and stored pollen, the highest mean of sealed brood area and stored pollen was found in colonies fed on mixture pollen, while the control had the lowest values. Feeding honey bee colonies on mixed pollen diet, broad bean and clover pollen gave the highest rate of population, with no significant differences (p<0.05). Supplying cage bees with different types of pollen had significant (p<0.05) differences on longevity. The bees that were fed on the mixture pollen lived for the longest possible period 30.63 days, followed by clover, broad bean, date palm and maize pollens (29.47, 26.22, 25.20 and 23.63 days, respectively). Also, it was noticed that feeding caged bees on sugar syrup only (control) shortened the longevity of honey bee workers (19.3 days only). This effect on longevity may be due to the phytochemical compounds that pollen contains, such as total antioxidants, including phenols, flavonoids, and tannins.
Structural , Optical , and Magnetic Properties of Nickel Oxide Nanoparticles Through Precipitation Method

Recently, investigated the most important inorganic material is nickel oxide nanoparticles (NiO NPs). The NiO is an essential material that can be widely used in many applications, such as capacitor, solar cell, and rechargeable lithium ion batteries. The NiO is one of the p-type semiconductor materials with wide band gap of 3.6-4 eV [1]. The magnetic nanoparticles are most widely utilized in conducting paints [2], rechargeable batteries [3], chemical catalysts [4], optoelectronics [5], magnetic recording media [6], Ferro-fluids [7] and drug delivery so on. In addition, NiO NPS have attracted and great attention because of their thermal applications and their specific chemical and physical properties [8]. Among the various nanomaterials, NiO nanomaterials exhibit significantly chemical, electronic, thermal, mechanical, magnetic, catalytic properties and optical properties in comparison with their bulk materials and have been extensively attracted application. Nowadays the pathogenic bacteria cause many diseases in human beings. NiO nanoparticles exhibit a higher antibacterial activity versus S.Sivakumar 1 , Nazir Ahmad Mala 2
MINAT ADOPSI ICT DI BIDANG AGRIBISNIS DI JAWA TIMUR: EMPIRICAL STUDY MENGGUNAKAN HIERARCHICAL LOGISTIC REGRESSION MODELLING

Penelitian ini bertujuan untuk merekonstruksi faktor-faktor pengaruh adopsi ICT di bidang agribisnis di Jawa Timur. Banyaknya sampel dalam penelitian ini adalah 200 agribisnis manager yang dijadikan sumber data primer. Disain dari penelitian ini mengacu pada model Y&J ICT Adoption Penelitian ini dikerjakan dalam dua tahap yaitu tahap descriptive development dan tahap hypotheses testing. Close questionaire didistribusikan kepada 150 responden dengan tingkat pengembalian 0.83% atau sebanyak 124 respon. Data kemudian diolah menggunakan analisis descriptive statistics, Confirmatory Factor Analysis dan Hierarchical Logistic Regression. Dengan reference category Y&J Adoption Level I (telephone) hasil Hierarchy Logit menunjukkan bahwa pada Wave I Wave II dan Wave III variable Literacy masih berpengaruh signifikan pada adopsi ICT level II (Computer) maupun Level III (Internet). Wave III memiliki varian variable yang signifikan yaitu dengan adanya variabel infrastruktur pada adopsi Level II (Computer) Serta Variabel Techshop pada adopsi level III (Internet). Kontribusi dari penelitian ini adalah pengembangan teori analisis regresi dalam penelitian sosial dengan mengedepankan model regresi non linier yang mampu mengakomodasi segala jenis data dengan metode hierarchi untuk mendapatkan kombinasi faktor pengaruh dan sekaligus sebagai alternatif pengganti metode Structural Equation Modelling. Bagi pengambil keputusan, hasil penelitian ini diharapkan mampu memberi kontribusi dalam mengidentifikasi kombinasi variable pengaruh adopsi pada berbagai gelombang (Waves). Sampel yang lebih besar diperlukan untuk memperbaiki performa output dan hasil analisis.
Innovations in Undergraduate Teaching and Learning of Earth and Environmental Science, with a Focus on Climate Change

Vol. 51, No. 4, 2022 T he quality of undergraduate education has been a matter of concern among policy and research institutions for some time (Association of American Universities [AAU], 2018; National Research Council [NRC], 2012, 2011; Zusman, 1999; Boyer Commission on Educating Undergraduates in the Research University [Boyer Commission], 1998). According to many of the metrics used by institutions of higher education (IHEs)—such as course enrollment, number and completion of STEM majors, and student learning and engagement (National Academies of Sciences, Engineering, and Medicine [NAS], 2018b; Eagan, 2016; Ferrare & Lee, 2014)—STEM education discourages too many undergraduates from remaining in their field of interest and remains predominantly lecture-based (Stains et al., 2018). Policy documents (e.g., President’s Council of Advisors on Science and Technology [PCAST], 2012; Beichner et al., 2007; Boyer Commission, 1998) draw on the learning sciences to advocate for “evidence-based” methods that will renew undergraduate education. Generally, these include curriculum redesign and pedagogical methods that attend to student engagement and agency. In this article, we examine the education research literature between Innovations in Undergraduate Teaching and Learning of Earth and Environmental Science, with a Focus on Climate Change
Ontology Specifications to Generate Questions

Ontology have been used across multiple fields. This paper investigates the use of ontology to generate quality questions. This project aims to define a set of specifications on an ontology for it to generate instances of different question types. In this way, higher quality, in the aspects of syntax, semantics and ontology-answerable questions can be generated. A software program was developed to generate questions from an ontology and a list of question templates. The resulting questions were evaluated for their quality and the feed-back was analysed. These results show that only small portion of the generated questions were good quality. The feedback provides several reasons with regards to the poor quality of the generated questions. Some of these reasons are the lack of scenario identified to cover different cases of generation for the same template, the incorrect use of axioms when generating questions and syntax errors when defining the templates.
The Lineup Protocol: Using Simulation to Improve Model Diagnostics in Binary Logistic Regression

Visual and numeric diagnostics for logistic regression frequently work with group-level data instead of individual observations. This leads to diagnostics that are well deﬁned for binomial logistic regression where data are grouped but that can break down in binary logistic regression where there are no groups. This article explores how simulation-based diagnostics can be applied to binary logistic regression to remedy this problem. In particular, we conduct a study to estimate the power of the lineup protocol, a particular simulation-based diagnostic. We discover that the lineup protocol is more powerful than a goodness-of-ﬁt test when data violate the independence assumption of logistic regression but less powerful when data violate the log-odds linearity assumption.
LRP-Based Argumentative Explanations for Neural Networks

In recent years, there have been many attempts to combine XAI with the field of symbolic AI in order to generate explanations for neural networks that are more interpretable and better align with human reasoning, with one prominent candidate for this synergy being the sub-field of computational argumentation. One method is to represent neural networks with quantitative bipolar argumentation frameworks (QBAFs) equipped with a particular semantics. The resulting QBAF can then be viewed as an explanation for the associated neural network. In this paper, we explore a novel LRP-based semantics under a new QBAF variant, namely neural QBAFs (nQBAFs). Since an nQBAF of a neural network is typically large, the nQBAF must be simplified before being used as an explanation. Our empirical evaluation indicates that the manner of this simplification is all important for the quality of the resulting explanation.
An Analysis of Occupational Classification in India: An Evidence from Labour Force Survey

Occupation plays a crucial role in the livelihood of an individual and a household for their survival. India is a very diverse country and so has several types of occupations available to employ. However, the classification of the occupations has certain patterns and specificity in the sense of regions, gender, caste, and class. In this paper, an analysis has been performed for several occupational groups across the sector (rural-urban) and sex (malefemale) based on the several age groups to understand the dynamics of occupations with respect to the age categories. For the purpose, the first periodic labour force survey 2017-18 has been used along with the ‘one’ digit code of national classification of occupation2004. This study is analytical and descriptive. The result finds the existence of rural-urban and male-female dimensions in the choice of occupation across the age groups of an individual. Most of the workers are employed in agriculture occupations, especially in the rural sector. The median age of a worker is highly concentrated for the age group of 30-44 years. A significant proportion of workers are still occupied in several occupations even after 60 years and old. This implies the need for a policy suggestion to increase the retirement age proportional to several occupations.
CircCCT 3 Acts as a Sponge of miR-613 to Promote Tumor Growth of Pancreatic Cancer Through Regulating VEGFA / VEGFR 2 Signaling

Pancreatic cancer (PC) is one of the most lethal malignancies and aggressive gastrointestinal tumors, remaining at the lowest 5-year relative survival rate of 9%. 1 Since its aggressive nature, late diagnosis, and limitations of existing chemo and radiation therapies, PC has become the fourth leading cancer type in estimates of the cause of death, and has been predicted to become the second cause of cancer-related deaths in developed countries by 2030.2 Therefore, understanding the potential mechanism that promotes PC progression is vital for developing effective diagnostic techniques and therapeutic strategies.