bluuebunny/crossref_metadata_2025_split huggingface dataset:
Production of V‐Doped P2‐type Na0.67Mn0.5Fe0.43Al0.07O2Cathodes and Investigation of Na‐Ion Full Cells Performance
Authors: Dogan Ebru , Altundag Sebahat , Altin Serdar , Arshad Muhammad , Balci Esra , Altin Emine 
Published: November 2023

The Na0.67Mn0.5−xVxFe0.43Al0.07O2(x= 0–0.1) samples are successfully produced and their structural properties are investigated by common techniques. The highest surface area is found as 4.94 m2 g−1forx = 0.04 V by the Brunauer–Elmet–Teller analysis. According to X‐ray photoelectron spectroscopy ofx = 0.04 V‐doped sample,V4+,and V5+ions are formed in the structure. The main phase is observed as P63/mmc symmetry with an impurity phase of V6O13forx ≥ 0.06 . According to the CV analysis, while the redox voltage decreases for the Mn3+/Mn4+, the intensity of the peaks of Fe2+/Fe3+redox reaction decreases. While the best capacity value of the half cells at C/3‐rate is obtained as 171 mAh g−1forx = 0.04, the lowest capacity fade is found forx = 0.08 . It is mentioned the V6O13may contribute to the electrochemical process . The galvanostatic tests are investigated for the voltage windows of 3.5–1.5, 4–1.5, 4–2.5, 4–2, and 4–2.5 V and it is seen that the battery cells for 3.5–1.5 V have the best capacity fade (6%) among the others. The Na0.67Mn0.46V0.04Fe0.43Al0.07O2/ hard carbon is used for the full cells with presodiated anode and the first capacity value of the full cell is obtained as 80.2 mAh g−1for C/2‐rate.
Large language model applications for evaluation: Opportunities and ethical implications
Authors: Head Cari Beth , Jasper Paul , McConnachie Matthew , Raftree Linda , Higdon Grace 
Published: November 2023

AbstractLarge language models (LLMs) are a type of generative artificial intelligence (AI) designed to produce text‐based content. LLMs use deep learning techniques and massively large data sets to understand, summarize, generate, and predict new text. LLMs caught the public eye in early 2023 when ChatGPT (the first consumer facing LLM) was released. LLM technologies are driven by recent advances in deep‐learning AI techniques, where language models are trained on extremely large text data from the internet and then re‐used for downstream tasks with limited fine‐tuning required. They offer exciting opportunities for evaluators to automate and accelerate time‐consuming tasks involving text analytics and text generation. We estimate that over two‐thirds of evaluation tasks will be affected by LLMs in the next 5 years. Use‐case examples include summarizing text data, extracting key information from text, analyzing and classifying text content, writing text, and translation. Despite the advances, the technologies pose significant challenges and risks. Because LLM technologies are generally trained on text from the internet, they tend to perpetuate biases (racism, sexism, ethnocentrism, and more) and exclusion of non‐majority languages. Current tools like ChatGPT have not been specifically developed for monitoring, evaluation, research, and learning (MERL) purposes, possibly limiting their accuracy and usefulness for evaluation. In addition, technical limitations and challenges with bias can lead to real world harm. To overcome these technical challenges and ethical risks, the evaluation community will need to work collaboratively with the data science community to co‐develop tools and processes and to ensure the application of quality and ethical standards.
Disrupting evaluation? Emerging technologies and their implications for the evaluation industry
Authors: Nielsen Steffen Bohni 
Published: November 2023

AbstractThis article surveyed different emerging technologies (ET), in particular artificial intelligence, and their burgeoning application in the evaluation industry. Evidence suggests that evaluators have been relatively slow in adopting ET in their practice. However, more recent data suggest that ET adoption is increasing. This article then analyzed if, and how, ET affect the evaluation industry and evaluation practice. The article finds that program evaluation is one of several competing forms of knowledge production informing decision‐making, particularly in the government and not‐for‐profit sectors. Therefore, evaluation faces a number of challenges stemming from ET. In this article, it is argued that evaluators must, albeit critically, embrace ET. Most likely, ET will complement evaluation practice and, in some instances, displace human tasks.
Vision for an equitable AI world: The role of evaluation and evaluators to incite change
Authors: Reid Aileen M. 
Published: November 2023

AbstractThe advent of generative AI such as ChatGPT has propelled the field of evaluation into conversations about the use of AI in the field and the ethics of knowledge generation. While there are many benefits of AI, as with any new technology there can be collateral damage. The discourse about AI and evaluation provides another opportunity to center equity in our work as evaluators by asking, how can evaluation contribute to the public good in an AI world? This article highlights contextual concerns with AI from an ecosystem perspective, placing emphasis on structural and racial/ethnic inequities, bias, and prejudice. The author issues a clarion call for the field of evaluation to act collectively to incite change by being proactive, embracing our professional responsibility and critical voice, and employing evidence‐based practice. Evaluators are encouraged to exercise our social and political responsibility through courageous leadership and advocacy to attend to the values of stakeholders and advance an equitable AI world.
A special delivery by a fork: Where does artificial intelligence come from?
Authors: Thornton Izzy 
Published: November 2023

AbstractIn this article, I discuss the use of artificial intelligence (AI) in evaluation and its relevance to the evolution of the field. I begin with a background on how AI models are developed, including how machine learning makes sense of data and how the algorithms it develops go on to power AI models. I go on to explain how this foundational understanding of machine learning and natural language processing informs where AI might and might not be effectively used. A critical concern is that AI models are only as strong as the data on which they are trained, and evaluators should consider important limitations when using AI, including its relevance to structural inequality. In considering the relationship between AI and evaluation, evaluators must consider both AI's use as an evaluative tool and its role as a new subject of evaluation. As AI becomes more and more relevant to a wider array of fields and disciplines, evaluators will need to develop strategies for how good the AI is (or is not), and what good the AI might (or might not) do.
Finding a safe zone in the highlands: Exploring evaluator competencies in the world of AI
Authors: Mason Sarah 
Published: November 2023

AbstractSince the public launch of ChatGPT in November 2022, disciplines across the globe have grappled with questions about how emerging artificial intelligence will impact their fields. In this article I explore a set of foundational concepts in artificial intelligence (AI), then apply them to the field of evaluation broadly, and the American Evaluation Association's evaluator competencies more specifically. Given recent developments in narrow AI, I then explore two potential frameworks for considering which evaluation competencies are most likely to be impacted—and potentially replaced—by emerging AI tools. Building on Moravec's Landscape of Human Competencies and Lee's Risk of Replacement Matrix I create an exploratory Landscape of Evaluator Competencies and an Evaluation‐Specific Risk of Replacement Matrix to help conceptualize which evaluator competencies may be more likely to contribute to long‐term sustainability for the field. Overall, I argue that the interpersonal, and contextually‐responsive aspects of evaluation work—in contrast to the more technical, program management, or methodological aspects of the field—may be the competencies least likely to be impacted or replaced by AI. As such, these may be the competencies we continue to emphasize, both in the day‐to‐day aspects of our operations, and in the training of new and emerging evaluators. This article is intended to be a starting point for discussions that continue throughout the remainder of this issue.
Artificial intelligence and the future of evaluation education: Possibilities and prototypes
Authors: Tilton Zach , LaVelle John M. , Ford Tian , Montenegro Maria 
Published: November 2023

AbstractAdvancements in Artificial Intelligence (AI) signal a paradigmatic shift with the potential for transforming many various aspects of society, including evaluation education, with implications for subsequent evaluation practice. This article explores the potential implications of AI for evaluator and evaluation education. Specifically, the article discusses key issues in evaluation education including equitable language access to evaluation education, navigating program, social science, and evaluation theory, understanding evaluation theorists and their philosophies, and case studies and simulations. The paper then considers how chatbots might address these issues, and documents efforts to prototype chatbots for three use cases in evaluation education, including a guidance counselor, teaching assistant, and mentor chatbot for young and emerging evaluations or anyone who wants to use it. The paper concludes with ruminations on additional research and activities on evaluation education topics such as how to best integrate evaluation literacy training into existing programs, making strategic linkages for practitioners, and evaluation educators.
Impact of the COVID‐19 pandemic on delivery of prostate cancer care in Australia: An interrupted time series analysis
Authors: Ng Hung Shin Brian , Tan Samuel , Rhee Handoo , Chung Eric 
Published: November 2023

AbstractThe COVID‐19 pandemic led to a major disruption to health services across the world. The aim of this population‐based study was to assess the downstream effects of the pandemic on diagnostic tests and treatment activities related to prostate cancer (PC). The Australian Government Department of Health Medicare Benefits Schedule and the Pharmaceutical Benefits Scheme databases were queried from January 2010 to June 2022. Two interrupted time series were performed Pre‐COVID (January 2010 to February 2020) and peri‐COVID (March 2020 to June 2022). Temporal modeling was performed to account for seasonal variation. Pre‐COVID‐19, monthly prostate‐specific antigen (PSA) testing showed a declining trend and testing decreased by 81 tests per 100 000 annually. A single‐month 38% drop in PSA testing was observed in April 2020; this corresponded to Australia's first wave. No change was observed in the rate of prostate biopsies. Peri‐COVID‐19 outbreaks, there was a slight shift toward the use of long‐acting androgen deprivation therapy (ADT) at 4% with a predilection still for short‐acting agents. with no registered change in the overall volume of radiotherapy or surgery. There were no deficits in the number of diagnostic and treatment activities for men with PC. Aside from a slight shift toward long‐acting ADT use during the pandemic, no other patterns were observed. The longer‐term impact such as missed diagnosis or late presentation affecting chances of survival due to COVID‐19 is yet to be ascertained.
Men don't cry: The supporting role as necessary for women's well‐being after termination of pregnancy
Authors: Alexopoulos Johanna , Tmej Anna , Naderer Andrea , Grussmann Magdalena , Tordy Karin , Stammler‐Safar Maria , Feichtinger Karin , Gipperich Andrea , Leithner Katharina 
Published: November 2023

AbstractObjectivesThe present study investigated similarities and differences of grief between men and women as part of the parental couple 1 year after termination of pregnancy (TOP) following a diagnosis of fetal anomaly.MethodsWe applied a method triangulation approach. We assessed several aspects of perinatal grief, depressive symptoms, posttraumatic stress, and anxiety as well as health‐related quality of life. In addition, we conducted qualitative interviews with the men to explore the fathers' roles in the partnership during pregnancy, the time of the diagnosis, TOP, and afterwards.ResultsWomen showed a more elevated grief response compared with men. Qualitative data revealed that men in our sample were mainly concerned with their partners' well‐being and concentrated on supporting their partners rather than on their own emotions. In addition, the supportive role of the male partner plays a central role in the well‐being of women and the man's coping with the situation.ConclusionIn clinical work, but also when developing new questionnaires, the specific role of the male partners needs to be considered more thoroughly. Particular attention should be paid to identify the men who find it difficult to assume the supporting role.
Dual‐logic‐in‐memory implementation with orthogonal polarization of van der Waals ferroelectric heterostructure
Authors: Niu Jingjie , Jeon Sumin , Kim Donggyu , Baek Sungpyo , Yoo Hyun Ho , Li Jie , Park Ji‐Sang , Lee Yoonmyung , Lee Sungjoo 
Published: November 2023

AbstractThe rapid advancement of AI‐enabled applications has resulted in an increasing need for energy‐efficient computing hardware. Logic‐in‐memory is a promising approach for processing the data stored in memory, wherein fast and efficient computations are possible owing to the parallel execution of reconfigurable logic operations. In this study, a dual‐logic‐in‐memory device, which can simultaneously perform two logic operations in four states, is demonstrated using van der Waals ferroelectric field‐effect transistors (vdW FeFETs). The proposed dual‐logic‐in‐memory device, which also acts as a two‐bit storage device, is a single bidirectional polarization‐integrated ferroelectric field‐effect transistor (BPI‐FeFET). It is fabricated by integrating an in‐plane vdW ferroelectric semiconductor SnS and an out‐of‐plane vdW ferroelectric gate dielectric material—CuInP2S6. Four reliable resistance states with excellent endurance and retention characteristics were achieved. The two‐bit storage mechanism in a BPI‐FeFET was analyzed from two perspectives: carrier density and carrier injection controls, which originated from the out‐of‐plane polarization of the gate dielectric and in‐plane polarization of the semiconductor, respectively. Unlike conventional multilevel FeFETs, the proposed BPI‐FeFET does not require additional pre‐examination or erasing steps to switch from/to an intermediate polarization, enabling direct switching between the four memory states. To utilize the fabricated BPI‐FeFET as a dual‐logic‐in‐memory device, two logical operations were selected (XOR and AND), and their parallel execution was demonstrated. Different types of logic operations could be implemented by selecting different initial states, demonstrating various types of functions required for numerous neural network operations. The flexibility and efficiency of the proposed dual‐logic‐in‐memory device appear promising in the realization of next‐generation low‐power computing systems.image
The relationship between cognitive and affective control and adolescent mental health
Authors: Minihan Savannah , Kumle Levi , Maston Kate , Bal Debopriyo , Werner‐Seidler Aliza , Christensen Helen , Schweizer Susanne 
Published: November 2023

AbstractBackgroundCognitive control problems have been implicated in the etiology and maintenance of mental health problems, including depression, in adults. Studies in adolescents have been more equivocal, with some showing changes in cognitive control in adolescents with mental health problems, whereas others fail to show an association. This study examines whether adolescent mental health is associated with affective control, the application of cognitive control in affective contexts, which shows more protracted development than cognitive control.MethodsThe present study investigated the association of cognitive and affective control with depressive symptomatology and self‐reported diagnostic history of mental health problems in adolescents. The study included 1929 participants (Mage = 13.89) from the Future Proofing Study (N = 6,388, 11–16 years), who completed affective (incl., affective stimuli) and/or cognitive (incl., neutral stimuli) versions of a working memory (backward digit‐span) and/or shifting (card‐sorting) task at least once within 3 weeks of assessing mental health.ResultsPoorer working memory was associated with greater depressive symptomatology in adolescents (β = −0.06, p = .004), similarly across cognitive and affective control conditions (β = −0.02, p = .269). Adolescents with self‐reported diagnostic history of mental health problems had significantly poorer shifting ability in affective compared to cognitive control conditions (b = 0.05, p = .010), whereas for adolescents with no self‐reported diagnoses, shifting ability did not differ between conditions (b = −0.00, p = .649).ConclusionsThe present analyses suggest that working memory difficulties, in particular, may be associated with the experience of current depressed mood in adolescents. Problems with affective shifting may be implicated in a range of mental health problems in adolescents. Given the ubiquitous need for efficient cognitive functioning in daily life, enhancing cognitive and affective control in adolescents may be a promising means of improving functioning across a range of domains, including affective functioning, and by extension, adolescent mental health.
Impacts of storage practices on the physical, culinary and sensory quality of Kponan yam (Dioscorea cayenensis‐rotundata) from Côte d'Ivoire during storage
Authors: Kouassi Kouakou Nestor , Kouadio Yapo Hypolithe , Kouassi Kouadio Benal , N'Dri Yao Denis , Amani N'Guessan Georges 
Published: November 2023

AbstractBACKGROUNDKponan is the most popular yam (Dioscorea cayenensis‐rotundata) variety in Côte d'Ivoire. Unfortunately, losses due to rotting during storage do not ensure a regular supply to markets. This study aimed to identify the impacts of cultivation and storage practices in the main production areas on physical, cooking and sensory characteristics of Kponan. To this end, yams grown in Bondoukou were stored in straw huts, those grown in Bouna in pits and those grown in Kouassi‐Kouassikro in the open air, according to the practices of each producer.RESULTSFindings showed that yams grown in Kouassi‐Kouassikro and stored in the open air recorded the highest rot rate (58.09%) compared to the rot rate of yams grown and stored in pits in Bouna (26.67%) and those grown and stored in straw huts in Bondoukou (53.34%). However, the weight losses were respectively 10.47% (Bouna), 28.57% (Kouassi‐Kouassikro) and 36.19% (Bondoukou). Loss rates varied significantly from 43.80% (pits) to 100% (huts and open air). Furthermore, the browning indices were higher for yams grown in Kouassi‐Kouassikro and freshly harvested (26.09) compared to the browning index recorded for yams grown and freshly harvested in Bouna (23.43) and in Bondoukou (24.73). Concerning the hardness of yams, it decreased during storage for yams grown and stored in pits in Bouna (38.94 to 25.20 N) and for those grown and stored in straw huts in Bondoukou (39. 39 to 26.42 N).CONCLUSIONThe shelf life and culinary and sensory characteristics of Kponan depend on the cultivation and storage practices of each producer. © 2023 Society of Chemical Industry.
Thermosensitive polymer‐assisted extraction and purification of fungal laccase from citrus pulp wash effluent
Authors: Santana Carlos E. M. , Barros Gabriela P. , Canuto Nathalia S. , dos Santos Tairan E. , Bharagava Ram N. , Liu Jiayang , Ferreira Luiz F. R. , Souza Ranyere L. 
Published: November 2023

AbstractBACKGROUNDThis study explores the use of liquid–liquid extraction with thermosensitive polymers for producing laccase (Lac) from Pleurotus sajor‐caju. This process leverages liquid waste from the citrus industry, specifically pulp wash. The research delves into extractive fermentation and thermoseparation, both processes being facilitated by a polymer exhibiting a lower critical solution temperature transition.RESULTSKey factors considered include the choice of polymer, its concentration, pH, separation temperature, and the behavior of the polymer‐rich phase post‐extractive fermentation concerning the lower critical solution temperature. Notably, under conditions of 45% by weight of Pluronic L‐61 and pH 5.0 at 25 °C, the Lac resulted in an enhancement in the purification factor of 28.4‐fold, compared with the Lac obtained directly from the fermentation process on the eighth day. There was an 83.6% recovery of the Lac enzyme in the bottom phase of the system. Additionally, the unique properties of Pluronic L‐61, which can induce phase separation and also allow for thermoseparation, led to a secondary fraction (aqueous solution) of Lac with purification factor of 2.1 ± 0.1‐fold (at 32 ± 0.9 °C and 30 ± 0.3 min without stirring) from the polymeric phase (top phase). Fourier‐transform infrared analysis validated the separation data, particularly highlighting the α‐helix content in the amide I region (1600–1700 cm−1).CONCLUSIONIn summary, the insights from this study pave the way for broader industrial applications of these techniques, underscoring benefits like streamlined process integration, heightened selectivity, and superior separation efficacy. © 2023 Society of Chemical Industry.
Highly reliable a‐Si:H gate driver on array with complementary double‐sided noise‐eliminating and dual voltage levels for TFT‐LCD applications
Authors: Zheng Guang‐Ting , Liu Po‐Tsun , Chen Jo‐Lin , Li Cheng‐Hao 
Published: November 2023

AbstractIn this work, we present a high‐reliability gate driver on array (GOA) for a 10.7‐in. HD (1,280 × RGB × 720) TFT‐LCD panel, featuring an alternatively double‐sided noise‐eliminating function. The gate driver circuit is designed with 12‐phase clock signals that exhibit 75% signal overlapping, threshold voltage recovering, and double‐sided driving schemes. The double‐sided driving scheme reduces the number of mental wires and TFTs in the gate driver circuit, resulting in a smaller layout area for GOA. By utilizing dual levels of voltage, we implemented a negative gate bias method to mitigate threshold voltage shifts for the noise‐eliminating and driving TFTs. This prevents the noises from clock signals effectively. The reliability test of the proposed GOA with 720 stages passed a strict testing condition (90°C and −40°C) for simulation and exhibited good performance over 800 hours at 90°C for measurement.
Noninvasive multichannel urodynamic system: Obtaining cutaneous electrical signals from the human urinary bladder
Authors: Kurniawan Jonas F. , Lee Sanghee , Le Hoang‐Kim , Nguyen Andrew K. L. , Sit Nathan L. J. , Pham Timothy , Tjhia Boris , Gottlieb Ryan , Li Carleen , Shin Andrew J. , Garcia Hassler Bueno , Wu Vincent M. , Mendoza Tris R , DiPina Thomas , Ornelas Gladys , Chiang George , Jamieson Christina A. M. , Santiago‐Lastra Yahir , Coleman Todd P. 
Published: November 2023

AbstractWe developed a high‐resolution and noninvasive multichannel urodynamic system combined with a novel signal‐processing algorithm tailored to extract electromyographic (EMG) activity from the urinary bladder. We utilized a flexible noninvasive biopotential recording system to collect an array of EMG signals from the urinary bladder of human subjects. This study also presents the use of an existing artifact rejection methodology to autonomously extract an EMG signal from an environment prone to motion artifacts.