Miracle-dz/UniFAR-FTUs huggingface dataset:
Which Aspect of Patient–Provider Relationship Affects Acceptance and Adherence of Insulin Therapy in Type 2 Diabetes Mellitus? A Qualitative Study in Primary Care

Purpose In type 2 diabetes mellitus (T2DM), insulin therapy is often recommended to achieve the optimal control of disease, thereby preventing the onset and progression of diabetes-related complications. Despite knowing about the benefits, it has been reported that 71% of patients refuse insulin and the adherence rate ranges from 30 to 80%. Patient–provider relationship (PPR) may affect such insulin-related behaviours, but little is known about which aspect of PPR affects this. This study aimed to explore the key aspect of the patient–provider relationship that affects the initial insulin acceptance and continued adherence. Patients and Methods We used the grounded theory approach in this qualitative research. The study was conducted at two primary care clinics between September 2019 and January 2021. Patients with T2DM on basal or premixed insulin were recruited using maximum variation sampling. Data were collected using semi-structured in-depth interviews and transcribed verbatim for analysis using constant comparison and synthesis. Results Twenty-one participants with different levels of diabetes control and adherence were recruited. Four themes that emerged were 1) patient–provider interaction, 2) addressing the psychological fears, 3) gaining confidence in handling insulin equipment and 4) follow-up after insulin initiation. Among the subthemes, trust in doctors, provider’s communication skills, patient-centred decision-making and continuity of care positively influenced insulin acceptance and adherence. Conversely, fear of being judged by the provider hindered open communication around non-adherence. Various aspects of interaction with nurses helped in alleviating patient’s fear of injection and gaining confidence with the insulin equipment. Conclusion Many aspects of PPR affect insulin acceptance and adherence. Among these, gaining patients’ trust, effective patient–provider communication, patient-centred decision-making, and ensuring continuity of care improve both insulin acceptance and treatment adherence. Various interactions with nurses help in addressing fears surrounding injection and gaining acceptance towards insulin therapy. Patients’ fear of being blamed or judged by the provider negatively affects open communication around non-adherence.
Potential of Trichoderma spp. for Biocontrol of Aflatoxin-Producing Aspergillus flavus

The inhibitory action of 20 antagonistic Trichoderma isolates against the aflatoxigenic isolate A. flavus ITEM 9 (Af-9) and their efficacy in reducing aflatoxin formation in vitro were examined. Production of metabolites with inhibitory effect by the Trichoderma isolates was also investigated. Antagonistic effect against Af-9 was assessed by inhibition of radial growth of the colonies and by fungal interactions in dual confrontation tests. A total of 8 out of 20 isolates resulted in a significant growth inhibition of 3-day-old cultures of Af-9, ranging from 13% to 65%. A total of 14 isolates reduced significantly the aflatoxin B1 (AfB1) content of 15-day-old Af-9 cultures; 4 were ineffective, and 2 increased AfB1. Reduction of AfB1 content was up to 84.9% and 71.1% in 7- and 15-day-old cultures, respectively. Since the inhibition of Af-9 growth by metabolites of Trichoderma was not necessarily associated with inhibition of AfB1 production and vice versa, we investigated the mechanism of reduction of AfB1 content at the molecular level by examining two strains: one (T60) that reduced both growth and mycotoxin content; and the other (T44) that reduced mycotoxin content but not Af-9 growth. The expression analyses for the two regulatory genes aflR and aflS, and the structural genes aflA, aflD, aflO and aflQ of the aflatoxin biosynthesis cluster indicated that neither strain was able to downregulate the aflatoxin synthesis, leading to the conclusion that the AfB1 content reduction by these Trichoderma strains was based on other mechanisms, such as enzyme degradation or complexation. Although further studies are envisaged to identify the metabolites involved in the biocontrol of A. flavus and prevention of aflatoxin accumulation, as well as for assessment of the efficacy under controlled and field conditions, Trichoderma spp. qualify as promising agents and possible alternative options to other biocontrol agents already in use.
KubFBS: A fine‐grained and balance‐aware scheduling system for deep learning tasks based on kubernetes

The past decade witnessed a remarkable increase in deep learning (DL) workloads which require GPU resources to accelerate the training process. However, the existing coarse‐grained scheduling mechanisms are agnostic to information other than the number of GPUs or GPU memory, which results in performance degradation of DL tasks. Moreover, the common assumption held by the existing balance‐aware DL task scheduling strategies, a DL task consumes resources once it starts, fails to reduce resource contention, and further limits execution efficiency. To address these problems, this article proposes a fine‐grained and balance‐aware scheduling model (FBSM) which considers the resource consumption characteristic of the DL task. Based on FBSM, we propose customized GPU sniffer (GPU‐S) and balance‐aware scheduler (BAS) modules to construct a scheduling system called KubFBS. The experimental results demonstrate KubFBS accelerates the execution of DL tasks while improving the load balancing capability of the cluster.
Improvement on Voltage Control Strategy Used in Automatic Voltage Control System of Power Plant

The automatic voltage control(AVC) system is an important tool for improving the voltage management level,reducing network loss,and ensuring secure and stable operation of power system.To resolve the problem of great voltage fluctuation due to changes of the grid connection manner,a new adaptive variable step voltage control method based on the Boltzmann probability distribution formula is proposed,in which a fast approaching method is adopted according to the difference between the target and actual voltage to perform voltage regulation function.Simulation results show that with the proposed control method,the voltage is smooth and stable,the voltage error can be corrected to some extent,and the voltage fluctuation due to system impedance changes can be effectively prevented,thus avoiding the damage to the power equipment and improving the system's voltage stability level.
A novel particulate matter 2.5 concentration prediction model based on double-layer decomposition and feedback of model learning effect

Accurate and effective particulate matter 2.5(PM2.5) concentration prediction can provide early warning information for decision-making departments, so as to take governance and preventive measures. A combined model based on double-layer decomposition(DLD) and feedback of model learning effect for PM 2.5 concentration prediction is proposed in this paper. Firstly, ensemble empirical mode decomposition (EEMD) and variational mode decomposition (VMD) were used for double-level decomposition for the PM2.5 concentration series, to reduce the nonstationarity and nonlinearity of the concentration series and improve the predictability; Secondly, a Wavelet neural network (WNN) prediction model based on the feedback of model learning effect is established for the subsequence obtained by double-layer decomposition. Finally, the prediction results of each subsequence are superimposed to obtain the final prediction results. The case study shows that the prediction model proposed in this paper is scientific.
Critic‐only online adaptive learning based decentralized control schemes for nonlinear large‐scale systems

In this article, the decentralized control issues of nonlinear large‐scale systems are investigated via critic‐only adaptive dynamic programming learning methods. First of all, we build a specific relation between the decentralized control for interconnected subsystems and the optimal control for isolated subsystems. Then, we utilize neural networks (NNs) to implement a critic‐only online adaptive learning method. The stability analysis result provides the region of the online learning rate, and indicates the NN can approximate the optimal solution. Subsequently, it is proven that the small NN approximation errors cannot affect the system stability. Finally, the simulation examples verify the feasibility.
Apache Spark and MLlib-Based Intrusion Detection System or How the Big Data Technologies Can Secure the Data

Since the turn of the millennium, the volume of data has increased significantly in both industries and scientific institutions. The processing of these volumes and variety of data we are dealing with are unlikely to be accomplished with conventional software solutions. Thus, new technologies belonging to the big data processing area, able to distribute and process data in a scalable way, are integrated into classical Business Intelligence (BI) systems or replace them. Furthermore, we can benefit from big data technologies to gain knowledge about security, which can be obtained from massive databases. The paper presents a security-relevant data analysis based on the big data analytics engine Apache Spark. A prototype intrusion detection system is developed aimed at detecting data anomalies through machine learning by using the k-means algorithm for clustering analysis implemented in Sparks MLlib. The extraction of features to detect anomalies is currently challenging because the problem of detecting anomalies is not actively and exhaustively monitored. The detection of abnormal data can be effectuated by using relevant data that are already in companies’ and scientific organizations’ possession. Their interpretation and further processing in a continuous manner can sufficiently contribute to anomaly and intrusion detection.
Cochlear Implant Results in Older Adults with Post-Lingual Deafness: The Role of “Top-Down” Neurocognitive Mechanisms

To date, no clear specific cognitive predictors of speech perception outcome in older adult cochlear implant (CI) users have yet emerged. The aim of this prospective study was to increase knowledge on cognitive and clinical predictors of the audiological outcome in adult cochlear implant users. A total of 21 patients with post-lingual deafness, who were candidates for cochlear implantation, were recruited at the Department of Ear, Nose and Throat, University of Torino (Italy) and subjected to a pre-operatory neuropsychological assessment (T0) and an audiological examination after 12 months of implantation (T12). Patients who, at T12, had a 60 dB verbal recognition above 80%, were younger (z = −2.131, p = 0.033) and performed better in the Verbal Semantic Fluency Test at T0 (z = −1.941, p = 0.052) than subjects who had a 60 dB verbal recognition at T12 below 80%. The most significant predictors of the CI audiological outcome at T12 were age (β = −0.492, p = 0.024) and patients’ TMT-A performance at baseline (β = −0.486, p = 0.035). We conclude that cognitive processing speed might be a good predictor of the level of speech understanding in older adult patients with CI after one year of implantation.
Electrophoretic µPAD for Purification and Analysis of DNA Samples

In this work, the fabrication and characterization of a simple, inexpensive, and effective microfluidic paper analytic device (µPAD) for monitoring DNA samples is reported. The glass microfiber-based chip has been fabricated by a new wax-based transfer-printing technique and an electrode printing process. It is capable of moving DNA effectively in a time-dependent fashion. The nucleic acid sample is not damaged by this process and is accumulated in front of the anode, but not directly on the electrode. Thus, further DNA processing is feasible. The system allows the DNA to be purified by separating it from other components in sample mixtures such as proteins. Furthermore, it is demonstrated that DNA can be moved through several layers of the glass fiber material. This proof of concept will provide the basis for the development of rapid test systems, e.g., for the detection of pathogens in water samples.
My Life, My Story: Integrating a Life Story Narrative Component Into Medical Student Curricula

Introduction Medical students experience burnout, depersonalization, and decreases in empathy throughout medical training. My Life, My Story (MLMS) is a narrative medicine project that aims to combat these adverse outcomes by teaching students to interview patients about their life story, with the goal of improving patient-centered care competencies, such as empathy. Methods The MLMS project was started in the Veterans Affairs (VA) system and has since spread to dozens of VA sites. We adapted and integrated this project into the Warren Alpert Medical School of Brown University curriculum. As part of the required curriculum, first- and third-year medical students participated in a life story interview with a community-based volunteer or a patient in the inpatient hospital setting, transcribed the story, and reviewed the written story with the patient. We assessed student perceptions of the project, changes in empathy, and changes in burnout symptoms. Results A total of 240 students participated in this project. Students spent an average of 70.7 minutes interviewing patients. A majority of the students believed MLMS was a good use of time (77%), fostered connection with patients (79%), and was effective in recognizing patients’ thoughts and feelings (69%). Discussion To our knowledge, this is one of the first life story interview interventions to be implemented into a required medical school curriculum and outside the VA setting. MLMS may assist students in improving clinical empathy skills and create a structure for medical trainees to better understand their patients.
Interactions with soil fungi alter density dependence and neighborhood effects in a locally abundant dipterocarp species

Abstract Seedling recruitment can be strongly affected by the composition of nearby plant species. At the neighborhood scale (on the order of tens of meters), adult conspecifics can modify soil chemistry and the presence of host microbes (pathogens and mutualists) across their combined canopy area or rooting zones. At local or small spatial scales (on the order of one to few meters), conspecific seed or seedling density can influence the strength of intraspecific light and resource competition and also modify the density‐dependent spread of natural enemies such as pathogens or invertebrate predators. Intrinsic correlation between proximity to adult conspecifics (i.e., recruitment neighborhood) and local seedling density, arising from dispersal, makes it difficult to separate the independent and interactive factors that contribute to recruitment success. Here, we present a field experiment in which we manipulated both the recruitment neighborhood and seedling density to explore how they interact to influence the growth and survival of Dryobalanops aromatica, a dominant ectomycorrhizal tree species in a Bornean tropical rainforest. First, we found that both local seedling density and recruitment neighborhood had effects on performance of D. aromatica seedlings, though the nature of these impacts varied between growth and survival. Second, we did not find strong evidence that the effect of density on seedling survival is dependent on the presence of conspecific adult trees. However, accumulation of mutualistic fungi beneath conspecifics adults does facilitate establishment of D. aromatica seedlings. In total, our results suggest that recruitment near adult conspecifics was not associated with a performance cost and may have weakly benefitted recruiting seedlings. Positive effects of conspecifics may be a factor facilitating the regional hyperabundance of this species. Synthesis: Our results provide support for the idea that dominant species in diverse forests may escape the localized recruitment suppression that limits abundance in rarer species.
Endocarditis in the Emergency Department: A POCUS Case Series

Introduction Infectious endocarditis remains a difficult to diagnose entity in the emergency department. This is partially due to vague and non-specific presenting symptoms but also because the Major Duke criteria [1,2] are difficult to achieve in the timeframe of the standard emergency department visit. This can lead to diagnostic uncertainty and delay in treatment. Point of Care Ultrasound (POCUS) has grown significantly in the emergency setting and is now readily available in most departments [3]. Utilizing POCUS in this difficult subset of patients can successfully identify endocarditis earlier and lead to improved treatment times. Cases Each of the three cases in this report demonstrate an episode of care in which the patient presented with non-specific symptoms. In two, endocarditis was suspected, while in the third case there was significant distraction to make the diagnosis very difficult. In each case, POCUS was applied successfully confirming the diagnosis of endocarditis when added to the minor Duke criteria already present. This led to a confirmation of diagnosis up to 12 hours before formal confirmation during the patients’ admissions. Conclusion While this specific indication for POCUS is currently outside the core utilization in the ED, and significant limitations remain: i.e. unknown sensitivity, this series demonstrates that POCUS provides value in the work up of suspected endocarditis by confirming the diagnosis earlier. This series suggests that further research into the sensitivity of POCUS for endocarditis in the ED may be warranted.
Efficacy and safety of intravenous paricalcitol treatment in Chinese hemodialysis patients: a real-world database analysis.

BACKGROUND The aim of this retrospective observational study based on real-world data was to evaluate the efficacy and safety profile of paricalcitol in Chinese hemodialysis (HD) patients with secondary hyperparathyroidism (SHPT) in routine clinical practice. METHODS From the Better Life for Future database, a total of 668 Chinese hemodialysis patients from 104 dialysis centers between January 2015 and May 2019 were included in the analysis set. Intact parathyroid hormone (iPTH), total serum calcium (Ca), phosphate (P), dosage of intravenous (IV) paricalcitol (Zemplar®) were analyzed and discussed via retrospective analysis of the database during the treatment. RESULTS Patients were divided into five groups according to the duration of follow-up. Median iPTH levels decreased from 1,183 pg/mL at baseline to 676 pg/mL at the final visit, or 30.88% (P<0.0001). A total of 56.14% of patients had a ≥30% decrease and 29.34% of patients had a ≥50% decrease in iPTH level. Serum Ca levels shown significantly increased in the group of Month 12-24 (P=0.0479). Serum phosphate levels remained stable in all follow-up groups. The average dose of paricalcitol was 20±9 µg/week. The total dose of paricalcitol and baseline iPTH were negatively correlated with the decrease in iPTH levels. CONCLUSIONS This is the first national retrospective real-world observational study since intravenous paricalcitol is available in China since 2014. This study demonstrates the use of paricalcitol as an effective and well-tolerated treatment for the control of PTH during its use in routine practice.
Double Diffusive Magneto-Free-Convection Flow of Oldroyd-B Fluid over a Vertical Plate with Heat and Mass Flux

The purpose of this research is to analyze the general equations of double diffusive magneto-free convection in an Oldroyd-B fluid flow based on the fundamental symmetry that are presented in non-dimensional form and are applied to a moving heated vertical plate as the boundary layer flow up, with the existence of an external magnetic field that is either moving or fixed consistent with the plate. The thermal transport phenomenon in the presence of constant concentration, coupled with a first order chemical reaction under the exponential heating of the symmetry of fluid flow, is analyzed. The Laplace transform method is applied symmetrically to tackle the non-dimensional partial differential equations for velocity, mass and energy. The contribution of mass, thermal and mechanical components on the dynamics of fluid are presented and discussed independently. An interesting property regarding the behavior of the fluid velocity is found when the movement is observed in the magnetic intensity along with the plate. In that situation, the fluid velocity is not zero when it is far and away from the plate. Moreover, the heat transfer aspects, flow dynamics and their credence on the parameters are drawn out by graphical illustrations. Furthermore, some special cases for the movement of the plate are also studied.
Conjunctival Swab Real Time-PCR in Leishmania infantum Seropositive Dogs: Diagnostic and Prognostic Values

Simple Summary This 10-month-long study describes how conjunctival swab (CS) real time-PCR (qPCR) failed to be a useful diagnostic and prognostic test for canine leishmaniosis (CanL). From the beginning of the study (October 2020), a limited number of Leishmania infantum seropositive dogs remained CS qPCR positive in August 2021, and none of them developed an active CanL. Therefore, the detection of L. infantum kDNA by qPCR, even highly sensitive, may be considered “a random” if not accompanied by a significant clinical score for CanL and/or other direct diagnostic tests positivity. Hence, in seropositive dogs with CS qPCR positivity, sampling time and season variability of results should be considered. In this scenario, testing other significant biological samples (e.g., lymph node, bone marrow, and spleen), although invasive, is strongly advised. Abstract Conjunctival swabs (CS) are the most promising non-invasive samples for the diagnosis and the regular screening of Leishmania infantum infection in dogs although knowledge on their diagnostic performance is still inconclusive. This study evaluates CS real time-PCR (qPCR) analysis for the diagnosis of canine leishmaniosis (CanL) and its prognostic value in seropositive dogs from an endemic area. In October 2020 (T0), 26 dogs were enrolled, divided in two groups according to anti-L. infantum antibody titres (n = 13, group low titre (LT) and n = 13, group high titre (HT)), and followed-up in August 2021. At both timepoints, animals underwent clinical examination, complete blood count and biochemical analyses, and serological (indirect fluorescent antibody test) and molecular (CS and peripheral blood qPCR) testing. At T0, 10 out of 26 enrolled dogs were positive at CS qPCR, with the number of positive animals significantly higher in group HT than in LT. After 10 months, only 5 out of 21 dogs that completed the trial still tested CS qPCR positive, and none of them developed an active CanL based on clinical score and antibody titre. None of the dogs required any leishmanicidal and/or leishmaniostatic treatments. This prospective study showed unsatisfying diagnostic and prognostic performances of CS qPCR analysis in L. infantum seropositive asymptomatic dogs from an endemic area.
Adaptive error feedback regulator problem for 1‐D anti‐stable wave equation with distributed harmonic disturbance

In this article, we are concerned with the error feedback regulator design for a one‐dimensional anti‐stable wave equation with harmonic reference signal and distributed disturbance. By the tracking error of the left end displacement, we first introduce a transport equation and a transformation to transform the original wave system to an auxiliary system, where the displacement at the left end is a scaling of the tracking error of the original system. Then an adaptive error‐based observer is designed by using the tracking error to estimate the state of the auxiliary system and unknown amplitudes of the harmonic disturbance and reference signal. Next we propose an observer‐based error feedback controller to regulate the tracking error to zero asymptotically and keep all the states uniformly bounded. Finally some numerical results are presented to illustrate the effectiveness of the controller.