Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-analysis and Meta-regression of Cognitive Behavioral Therapy for Psychosis (CBTp) Across Time: The Effectiveness of CBTp has Improved for Delusions

Published research shows small-to-medium effects of Cognitive Behavioral Therapy for Psychosis (CBTp) on reducing psychotic symptoms. Given the on-going development of CBTp interventions, the aim of this systematic review is to examine whether the effectiveness of CBTp has changed across time. MEDLINE, EMBASE, PsycINFO, and CENTRAL were searched for randomized controlled trials examining CBTp interventions targeting positive and/or negative symptoms vs treatment as usual. Four meta-analyses were carried out to examine the effectiveness of CBTp for: positive symptoms; delusions; hallucinations; and negative symptoms. Four meta-regressions examined whether the effectiveness of CBTp changed across time for these groups of symptoms. A total of 28 studies (n = 2698) yielded a pooled g of −0.24 (95% confidence interval [CI] −0.32, −0.16, P < .001) favoring CBTp for positive symptoms, with nonsignificant heterogeneity (Q = 26.87, P = .47; I2 =0%); 13 studies (n = 890) yielded a pooled g of −0.36 (95% CI −0.59, −0.13, P = .002) for delusions, with substantial heterogeneity (Q = 31.99, P = .001; I2 =62%); 16 studies (n = 849) yielded a pooled g of −0.26 (95% CI −0.42, −0.11, P < .001) for hallucinations, with nonsignificant heterogeneity (Q = 18.10, P = .26; I2 =17%); 19 studies (n = 1761) yielded a pooled g of −0.22 (95% CI −0.33, −0.12, P < .001) for negative symptoms, with nonsignificant heterogeneity (Q = 20.32, P = .32, I2 =11%). Meta-regressions indicated a significant effect of year on the effectiveness of CBTp only for delusions (F[1, 11] = 5.99, P = .032; R2 = 0.594); methodological quality did not effect this finding. Findings indicate small-to-medium effects of CBTp for psychotic symptoms, with increasing effectiveness across time for delusions.
Effect of milk replacement by whey protein concentrates on the rheological properties of Dulce de Leche

Abstract The flow behaviour of commercial samples of Dulce de Leche (sweet milk spread) was determined as a model for the development of products containing ultrafiltration whey protein concentrate. The spreads followed the Herschel-Bulkley model with a flow behaviour index of 0.67 and a significant yield stress constant. The consistency coefficients and yield stress constants varied in a broad range. Samples prepared with a 50% replacement of milk proteins by whey proteins showed the same theological behaviour as the commercial product and could not be distinguished from those prepared exclusively with milk.
Social norms as anchor points for trust

ABSTRACT We investigate whether a social norm communication can be used to nudge decision makers towards increased trust. An experiment was conducted using a modified trust game, where subjects played two rounds of the game. Prior to the second round, a social norm of sending behaviour was communicated to participants. The impact of the social norm communication on trusting behaviour varied with initial transfers: For those who initially transferred amounts below this point, transfers (indicative of trust) increased. However, this impact was almost entirely offset by decreased transfers among those who had initially transferred amounts above this point, suggesting that the social norm communication acted as an anchor point towards which subsequent transfers were drawn. The result in our study was that mean trusting behaviour did not change significantly with the social norm communication. The net impact of an anchor point would be expected to vary with the distribution of behaviour prior to the social norm communication, risking a negative net impact in some cases. Our findings therefore suggest a need for caution in using broadly targeted social norm communications.
Antipredator defenses and the persistence of amphibian larvae with fishes

Communities of larval amphibians in fishless habitats often differ strikingly from those in habitats with fish. We surveyed larvae of 15 amphibian species to determine if presence or absence of specific defenses against fish was correlated with breeding habitat. Each species was tested for two key defenses: unpalatability and chemically mediated predator avoidance. In eight of nine cases, larvae of species that often encounter fish had at least one of these defenses. In contrast, larvae of seven species that breed in fishless pools consistently lacked defenses against fish. Lack of appropriate defenses appears to be a primary reason why temporary pool species cannot successfully coexist with predatory fishes in permanent habitats. Palatability and responses to chemical cues from fish often differed among closely related taxa and were correlated strongly with frequency of encounter with fish. Thus, natural selection rather than phylogeny best explains interspecific variation in antipredator defen- ses. Our data show that members of at least two orders and four families of amphibians use chemical cues to reduce predation risk from predatory fish.
Deep Reinforcement Learning-Based Controller for SOC Management of Multi-Electrical Energy Storage System

The ongoing reduction of the total rotational inertia in modern power systems brings about faster frequency dynamics that must be limited to maintain a secure and economical operation. Electrical energy storage systems (EESSs) have become increasingly attractive to provide fast frequency response services due to their response times. However, proper management of their finite energy reserves is required to ensure timely and secure operation. This paper proposes a deep reinforcement learning (DRL) based controller to manage the state of charge (SOC) of a Multi-EESS (M-EESS), providing frequency response services to the power grid. The proposed DRL agent is trained using an actor-critic method called Deep Deterministic Policy Gradients (DDPG) that allows for continuous action and smoother SOC control of the M-EESS. Deep neural networks (DNNs) are used to represent the actor and critic policies. The proposed strategy comprises granting the agent a constant reward for each time step that the SOC is within a specific band of its target value combined with a substantial penalty if the SOC reaches its minimum or maximum allowable values. The proposed controller is compared to benchmark DRL methods and other control techniques, i.e., Fuzzy Logic and a traditional PID control. Simulation results show the effectiveness of the proposed approach.
A Complete HSS-Based Impedance Model of MMC Considering Grid Impedance Coupling

Harmonic state space (HSS) is seen as an effective impedance modeling method to precisely characterize the internal harmonic features of the modular multilevel converter (MMC). However, the existing MMC impedance models assume the ideal grid, ignoring the grid impedance, and they also do not incorporate the widely used dual-loop control and phase-locked loop (PLL). In this article, a complete MMC impedance model based on HSS is proposed to reveal the grid impedance coupling effect of MMC. The model analysis results demonstrate that the MMC impedance is coupled with the grid impedance due to the internal harmonics. This coupling causes MMC to be affected by the grid impedance and may cause instability. On the other hand, the proposed model not only consists of the ac current and the circulating current control, but also incorporates dc voltage outer loop and PLL with a clear physical meaning. Based on the proposed model, this article illustrates the factors that will enhance the coupling, which shows that the proposed model has to be used to improve the accuracy of the analysis. Finally, effectiveness of the proposed model is verified by simulation and experimental results.
Support Vector Machine based eHealth Cloud System for Diabetes Classification

INTRODUCTION: Diabetes is a major health issue because it leaves people with physical disabilities. Therefore, methodologies with a reduced error rate must be used to diagnose this dangerous disease. Data Mining techniques such as Artificial Neural Network are common tools adopted for the classification of diabetes and one of the core components of the eHealth system. Data Mining techniques aim to provide reliable and timely diagnostic outcomes during the diagnosis of the disease. OBJECTIVE: The objective of the research work is to propose a Support Vector Machine based eHealth Cloud System for Diabetes Classification. This work aims to improve the diagnostic accuracy of computer-assisted diagnostic systems. METHOD: The proposed methodology implemented in two-phase, In the first phase system is trained using different Support Vector Machine (SVM) kernel functions and in the second phase effectiveness of the system is tested in terms of classification accuracy and error. Different SVMs have the ability to diagnose this disease. PIMA Indian Diabetes Dataset (PIDD) has been used in our experiments for training and testing. Kernel functions are usually used to refer to the kernel trick, a method of using a linear classifier to solve a non-linear problem. RESULT: In this classification accuracy and classification error are used for performance evaluation. It is worth mentioning that the system giving remarkable accuracy of 77.50% in Coarse Gaussian SVM in 10-fold validation whereas fine Gaussian SVM gives 98.8% accuracy in No validation set. CONCLUSION: This paper introduces the SVM eHealth Cloud System for Diabetes Classification. The system is trained using the PIDD. Such a system can be used as “Application-as-a-Service” in cloud computing. It is therefore believed that the system will enhance the process of clinical decision-making and also assist physicians concerning Diabetes Diagnosis. It is worth to mention that the SVM kernel-based system performed well in comparison to the different systems.
Organizational Communication Dynamics in the Process of Integrated Information System in Muhammadiyah Healthcare Charity Venture

As a progressing Islamic movement and one of the most prominent Islamic organizations, Muhammadiyah does not only focus on the religious field but also charity ventures in the fields of education, social, and health. Muhammadiyah's potential in developing its charity venture in the health sector is enormous. This study aims to analyze the dynamics of organizational communication in the process of coordinating the integration of the Muhammadiyah health information system. This qualitative research used a case study approach and in-depth interviews, observation, and archival documents, as the data collection technique. This research showed that the integration of health information systems in Muhammadiyah is challenging to realize due to the high potential of the sectoral ego in the process of managing the Muhammadiyah Healthcare Charity Venture (AUMKES). Supervising Council of General Wellbeing (MPKU) as an assembly responsible for planning, organizing, coordinating, and supervising the management of the health sector in Muhammadiyah needs to strengthen its capacity, especially in the area of organizational communication management. This is because MPKU PPM has not had enough power and legitimacy in uniting the perceptions of each RSMA manager.
A novel method for the classification of Alzheimer's disease from normal controls using magnetic resonance imaging

Alzheimer's disease (AD) is the most prevalent form of dementia. Although fewer people, who suffer from AD are correctly and promptly diagnosed, due to a lack of knowledge of its cause and unavailability of treatment, AD is more manageable if the symptoms of mild cognitive impairment (MCI) are in an early stage. In recent years, computer‐aided diagnosis has been widely used for the diagnosis of AD. The main motive of this paper is to improve the classification and prediction accuracy of AD. In this paper, a novel approach is developed to classify MCI, normal control (NC), and AD using structural magnetic resonance imaging (sMRI) from the Alzheimer's disease Neuroimaging Initiative (ADNI) dataset (50 AD, 50 NC, 50 MCI subjects). FreeSurfer is used to process these MRI data and obtain cortical features such as volume, surface area, thickness, white matter (WM), and intrinsic curvature of the brain regions. These features are modified by normalizing each cortical region's features using the absolute maximum value of that region's features from all subjects in each group of MCI, NC, and AD independently. A total of 420 features are obtained. To address the curse of dimensionality, the obtained features are reduced to 30 features using a sequential feature selection technique. Three classifiers, namely the twin support vector machine (TSVM), least squares TSVM (LSTSVM), and robust energy‐based least squares TSVM (RELS‐TSVM), are used to evaluate the classification accuracy from the obtained features. Five‐fold and 10‐fold cross‐validation are used to validate the proposed method. Experimental results show an accuracy of 100% for the studied database. The proposed approach is innovative due to its higher classification accuracy compared to methods in the existing literature.
Implementation of a Fractional-Order Electronically Reconfigurable Lung Impedance Emulator of the Human Respiratory Tree

The fractional-order lung impedance model of the human respiratory tree is implemented in this paper, using Operational Transconductance Amplifiers. The employment of such active element offers electronic adjustment of the impedance characteristics in terms of both elements values and orders. As the MOS transistors in OTAs are biased in the weak inversion region, the power dissipation and the dc bias voltage of operation are also minimized. In addition, the partial fraction expansion tool has been utilized, in order to achieve reduction of the spread of the required time-constants and scaling factors. The performance of the proposed scheme has been evaluated, at post-layout level, using MOS transistors models provided by the 0.35 μ m Austria Mikro Systeme technology CMOS process, and the Cadence IC design suite.
High Protein Rice Flour in the Development of Gluten-Free Bread

ABSTRACT There is a need for acceptable gluten-free foods that provide greater protein. Rice is used in gluten-free products and new higher protein rice varieties now exist. Stores surveyed for products with rice flour as the main ingredient showed 36% snacks and 13% breads, with baked snacks 1.3 g protein/serving. Bread was chosen as the focus for testing higher protein rice flour (HPR). HPR were compared to commercial rice flours (CW) for pasting properties, protein, fat, and fiber content. Gluten-free bread was prepared and tested for color and texture. A consumer sensory study rated appearance, aroma, texture, and taste of the breads. Brown and white HPR were 10.1% and 9.25% protein. There were no differences in acceptance of breads made with any flour. Health benefit information for HPR breads increased purchase intent. Rice flour with greater protein can be used in gluten-free rice flour baked goods without affecting properties.
Striking a balance between the literature load and walks in the woods

www.frontiersinecology. org © The Ecological Society of America Graduate students in ecology are busy with teaching, lab meetings, coursework, research, and having a life (however minimal) outside of the lab. While we have no choice about the amount of time we devote to some tasks (ie lab meetings are from three to four o’clock on Thursdays), prioritizing time spent mastering one’s study system versus keeping up with the current literature poses a dilemma. Should we be investing our time in observation of the study subjects, or should we be catching up on reading about cutting-edge topics in our discipline’s top journals? Our advisors would probably say we should do both, but there are only so many hours in the day to read papers and watch beetles, and, after a certain point, coffee is no substitute for sleep. While we do not claim to have any magic solutions, there are some tricks that can help graduate students to both stay current in new research and know their own systems. Keeping up with what’s hot (and what’s not) in ecological research is beneficial when it comes to grant funding, publishing in high-profile journals, and getting into spirited debates with other students at national meetings or the local pub. But a vast amount of new research comes out daily, either in print or online, and sifting through it can be a daunting task; Web of Science reports that more than 10 000 articles were published in ecological journals in 2005 alone! Then there are the classic papers that are just as important to know as the current ones. One way of staying current with new research is to have the table of contents from each new issue of your top 5–10 journals e-mailed to you. Be sure to dedicate time every week to reading through at least the titles and abstracts of relevant papers. This will help you to find the papers most pertinent to your research and will also fill you in on topics that other researchers are pursuing. Another way to keep on top of new literature is to subscribe to online citation alerts through Web of Science. These alerts are e-mailed weekly and list recently published papers that have cited other articles you specify. Sign up to receive citation alerts for the key papers in your field, so you can see who else cites that paper, and in FRESH PERSPECTIVES FRESH PERSPECTIVES
Secondarily reduced foreleg armature in Perochaeta dikowi sp.n. (Diptera: Cyclorrhapha: Sepsidae) due to a novel mounting technique

Abstract The males of almost all sepsid species have strongly modified forelegs that are used to clamp the female’s wingbase during mounting. Here, we describe a new species in the genus Perochaeta whose males have unmodified forelegs. We use DNA sequence data for ten genes to reconstruct the position of Perochaeta on the phylogenetic tree for Sepsidae, and reveal that the lack of foreleg armature in Perochaeta dikowi sp.n. is secondary. Through the study of the mating behaviour of the new species, we demonstrate that the loss of armature is correlated with a new mounting technique during which the males of P. dikowi do not use the foreleg to clamp the female’s wingbase. Instead, the male approaches the female from behind and bends his abdomen forwards in order to establish genital contact. Our study shows how data from morphology, phylogenetics, and behavioural biology can complement each other to yield a deeper understanding of how changes in morphology and behaviour are correlated.
Visualizing When, Where, and How Fires Happen in U.S. Parks and Protected Areas

Fire management in protected areas faces mounting obstacles as climate change alters disturbance regimes, resources are diverted to fighting wildfires, and more people live along the boundaries of parks. Evidence-based prescribed fire management and improved communication with stakeholders is vital to reducing fire risk while maintaining public trust. Numerous national fire databases document when and where natural, prescribed, and human-caused fires have occurred on public lands in the United States. However, these databases are incongruous and non-standardized, making it difficult to visualize spatiotemporal patterns of fire and engage stakeholders in decision-making. We created interactive decision analytics (“VISTAFiRe”) that transform fire history data into clear visualizations of the spatial and temporal dimensions of fire and its management. We demonstrate the utility of our approach using Big Cypress National Preserve and Everglades National Park as examples of protected areas experiencing fire regime change between 1980 and 2017. Our open source visualizations may be applied to any data from the National Park Service Wildland Fire Events Geodatabase, with flexibility to communicate shifts in fire regimes over time, such as the type of ignition, duration and magnitude, and changes in seasonal occurrence. Application of the tool to Everglades and Big Cypress revealed that natural wildfires are occurring earlier in the wildfire season, while human-caused and prescribed wildfires are becoming less and more common, respectively. These new avenues of stakeholder communication are allowing the National Park Service to devise research plans to prepare for environmental change, guide resource allocation, and support decision-making in a clear and timely manner.
Pteridophytes of Moorea, French Polynesia, with a New Species, Tmesipteris gracilis (Psilotaceae)

We examined collections of pteridophytes from Moorea and others of the Society Islands, as well as literature relevant to the pteridophytes of Polynesia. This resulted in a list of species known to occur on Moorea, along with a list of species reported for Moorea but lacking voucher specimens, and a list of species perhaps to be found on Moorea based on collections from nearby Tahiti and adjacent islands in the archipelago, at suitable elevations. We include habitat, locality, and appropriate taxonomic commentary for each known species. A new species in the family Psilotaceae, Tmesipteris gracilis Chinnock, is described from the Society and Marquesas Islands. We also include a discussion of pteridophyte collection history on Moorea and biogeographic notes for species on the island.
Floristic and Structural Composition of Wonderwoud Forest in the Wolkberg, North-Eastern Transvaal

SYNOPSIS The closed, evergreen forest of 450 ha was studied by means of a survey of 55 circular plots of 0,04 ha, distributed in a grid pattern. TWINSPAN classification separated the forest into four stand types: Olea capensis macrocarpa—Xymalos monospora—Syzygium gerrardii forest (types 1 and 2) and Cryptocarya liebertiana forest (types 3 and 4). The types differ from each other in terms of floristics, stem density, basal area, and diameter distribution of trees. Tree generation is generally sparse and small, and do not represent the present canopy composition. Regrowth species are generally lacking. A species list is appended.
How Do Low-Income People Form Survival Networks? Routine Organizations as Brokers

While supportive social ties help to buffer against the consequences of poverty, few researchers have examined how people form such ties. New ties are often formed in routine organizations such as businesses, churches, and childcare centers, which, beyond being places to work, shop, or receive services, are institutionally governed spaces of social interaction. Based on the notion of organizational brokerage, we introduce a perspective that specifies when routine organizations contribute to tie formation and use it to reexamine data from existing qualitative studies of such organizations among the poor. We argue that successful brokerage will depend on the degree to which an organization’s institutional norms render interaction among participants frequent, long-lasting, focused on others, and centered on joint tasks; and that the ensuing networks may differ from other supportive ties in the sense of belonging they may cultivate, the form of generalized exchange they may engender, and the organizational connections they may create.