Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Amiodarone and Cedilan in the Treatment of Patients with Arrhythmia after Esophageal and Lung Cancer

Objective To explore the effect of amiodarone and cedilan in the treatment of patients with arrhythmia after esophageal and lung cancer. Methods The data of 60 patients with postoperative complications of arrhythmias after esophageal and lung cancer from January 2018 to July 2021 were retrospectively analyzed and divided into an observation group (n = 30) and control group (n = 30) according to the random number grouping principle. The former group was treated with amiodarone, and the latter group received cedilan. Results The effective rate of treatment was significantly higher in the observation group than the control group (P < 0.05). The observation group had the drug onset time obviously shorter than the control group (P < 0.001). The average ventricular rate after treatment in the observation group was remarkably lower than the control group (P < 0.001). The observation group exhibited obviously better cardiac function after treatment as compared to the control group (P < 0.05). The incidence of adverse reactions in the observation group was notably lower than the control group (P < 0.05). Moreover, the observation group had less stress after treatment than the control group (P < 0.001). The blood pressure level of the observation group after treatment was significantly better than the control group (P < 0.05). Conclusion Amiodarone can relieve stress in patients with arrhythmia following esophageal and lung cancer surgery, stabilize blood pressure, and mitigate arrhythmia symptoms. Our findings are worthy of promotion and application in clinic.
Lights and Shadows on the Cancer Multi-Target Inhibitor Rigosertib (ON-01910.Na)

Rigosertib (ON-01910.Na) is a small-molecule member of the novel synthetic benzyl-styryl-sulfonate family. It is currently in phase III clinical trials for several myelodysplastic syndromes and leukemias and is therefore close to clinical translation. The clinical progress of rigosertib has been hampered by a lack of understanding of its mechanism of action, as it is currently considered a multi-target inhibitor. Rigosertib was first described as an inhibitor of the mitotic master regulator Polo-like kinase 1 (Plk1). However, in recent years, some studies have shown that rigosertib may also interact with the PI3K/Akt pathway, act as a Ras–Raf binding mimetic (altering the Ras signaling pathway), as a microtubule destabilizing agent, or as an activator of a stress-induced phospho-regulatory circuit that ultimately hyperphosphorylates and inactivates Ras signaling effectors. Understanding the mechanism of action of rigosertib has potential clinical implications worth exploring, as it may help to tailor cancer therapies and improve patient outcomes.
A simple method for developing near real-time nationwide forest monitoring for Indonesia using MODIS near- and shortwave infrared bands

ABSTRACT Regarding to the deforestation and forest degradation issue in Indonesia, it is an urgent need to develop near real-time forest monitoring that can be seen by the public to make sure the transparency of forest resources management. Remote-sensing technology seems to be a powerful tool for monitoring and assessing the changes in forest cover immediately. We explored 250 m multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) data sets to assign a change of temporal land surface dynamics based on two indices; normalized difference vegetation index (NDVI) and open area index (OAI). The data sets were filtered by two filtering approaches, median moving window and linear interpolation, in order to reduce the overall noise so as not to lose useful information from the time-series data. Our results indicated that the use of MODIS data as a basic information in the near real-time system offers great promise to detect the forest cover change in Indonesia’s forestland, since about 90.07% of area assigned to be a change area had actually changed. Meanwhile, about 34.97% of the forest cover change was not assigned to be a change area by the system. This result showed the need to evaluate the threshold in detecting forest cover change. Although the threshold issue is quite problematic in forest cover change detection, the results show that the methodology proposed in this study provides sufficient and useful information in forest monitoring; this includes the location, time and trajectories of the changes. The results of the detection system developed in this article will be available for potential users.
Use of factorial design in formulation and evaluation of intrarectal in situ gel of sumatriptan

The study's goal was to create an in situ intrarectal mucoadhesive gel of sumatriptan (SMT) combining mucoadhesive polymer (xyloglucan) and thermosensitive polymers (poloxamer 407 and poloxamer 188) to prolong rectal residence time for treatment of migraines. Nine SMT mucoadhesive rectal in situ gel (RIG) formulas were created by mixing poloxamer 407 (18%, 19%, or 20%) with poloxamer 188 (5%), a mucoadhesive polymer at various doses (0.1, 0.2, and 0.3) as well as SMT (25 mg/ml). The prepared suppositories underwent for mucoadhesive force, gelation temperature, and gelation time. When SMT and mucoadhesive polymer were added to the poloxamer mixture, the gelation temperature dropped; however, poloxamer 188 had the opposite effect. These polymers supported the prepared liquids' ability to adhere to mucous membranes and form a strong gel. The transition gelation temperature of the poloxamer solution rose as a result of the addition of poloxamer 188. The findings showed that the formula RIG5 which is composed of poloxamer 407 (19%), poloxamer 188 (5%), and xyloglucan (0.2%) had an ideal transition temperature of 36.33°C, gel strength of 44.66°C, mucoadhesive force of 6409°C, and in vitro drug release of 93.98% over an 8-hour period. In light of this, it can be said that SMT was successfully manufactured as RIG without causing any chemical reaction with its additives.
L-structured matrices and linear matrix equations

Conditions for the existence of solutions, and the general solution of linear matrix equations are given, when it is known a priori that the solution matrix has a given structure (e.g. symmetric, triangular, diagonal). This theory is subsequently extended to matrix equations that are linear in several unknown ‘structured’ matrices, and to partitioned matrix equations.
Plant Essential Oils as a Tool in the Control of Bovine Mastitis: An Update

Bovine mastitis is a major concern for the dairy cattle community worldwide. Mastitis, subclinical or clinical, can be caused by contagious or environmental pathogens. Costs related to mastitis include direct and indirect losses, leading to global annual losses of USD 35 billion. The primary treatment of mastitis is represented by antibiotics, even if that results in the presence of residues in milk. The overuse and misuse of antibiotics in livestock is contributing to the development of antimicrobial resistance (AMR), resulting in a limited resolution of mastitis treatments, as well as a serious threat for public health. Novel alternatives, like the use of plant essential oils (EOs), are needed to replace antibiotic therapy when facing multidrug-resistant bacteria. This review aims to provide an updated overview of the in vitro and in vivo studies available on EOs and their main components as an antibacterial treatment against a variety of mastitis causing pathogens. There are many in vitro studies, but only several in vivo. Given the promising results of treatments with EOs, further clinical trials are needed.
Generalized wavelet transforms and the cortex transform

This paper presents a generalization of the continuous wavelet transform to higher dimensions. This generalization includes previous higher dimensional generalizations as special cases, without the loss of the elegance of the one-dimensional equations. One noteworthy special case is a transform that is closely related to the cortex transform developed by Watson (1987). This special case firmly relates the cortex transform to wavelet theory. This paper emphasizes the utility of the theory by using it to derive an implementation of the cortex transform. The generalized wavelet analysis introduced in this paper encompasses three important special cases of wavelet analysis: one-dimensional wavelet analysis, rectilinear wavelet analysis, and circular wavelet analysis. The preliminary results presented demonstrate that the wavelet-based cortex transform adequately represents an image and reconstructs it from its representation, provided some care is taken in the implementation. <<ETX>>
Reflecting on intellectual capital measurement and management in European universities

Purpose This paper aims to critically review intellectual capital (IC) accounting research and practices in European public universities, specifically in Spain, Austria and Italy. These three countries represent the majority of IC accounting research related to universities. Design/methodology/approach This study critically reviews a selection of university-based IC accounting research, applying Alvesson and Deetz’s (2000) critical perspectives of insight, critique and transformative redefinition. Findings The analysis reveals that European public universities follow the Humboldtian model of higher education, integrating a third mission to society into their traditional roles as teaching and research institutions. This study explored how the emergence of a third mission for the university was conceptualised. This study also provided insights, critique and a transformative redefinition to advance IC as a strategic resource in European public universities. Originality/value The findings provide academics and policymakers with insights, critique and a transformative redefinition of IC as a strategic resource for European public universities to meet future challenges in an ever-changing world.
Risk Factors and Practices for the Development of Open Source Software From Developers’ Perspective

Open source software (OSS) has achieved popularity, however there are various software product quality problems, security issues and certain challenges confronting the OSS growth that need to be identified and addressed. The main focus of this research is to identify the risk factors associated with open-source software and the practices for those risks which will help software development companies and individuals to mitigate the risks. A systematic literature review (SLR) is employed for the identification of potential risk factors in OSS whereas questionnaire survey is used to validate the findings of the SLR from the relevant expert community. In the second round another SLR is carried out to identify the practices for softening the effect of risk-factors in OSS development. A total of 14 risk factors from the developers’ perspective are identified via SLR in OSS. Amid the risk factors identified bugs, insufficient product documentation, and lack of communication and coordination among developers are considered the most important Further, we performed a secondary SLR to identify the practices for mitigating the effects of the risk factors in OSS. Therefore, a total of 31 practices for mitigating and addressing the risk factors in OSS were identified. In this work, we identified 14 risk factors and 31 practices for mitigating the critical risk factors, through SLR for adapting OSS development from developers’ perspectives. We argue that focusing on the identified risk factors would minimize the risks associated with OSS. We also recommend that OSS developers should diligently consider all the risk factors that have been identified in the study for increased software productivity and distribution of reliable and robust source code.
Artificial Immune Linear Discriminant Analysis

In Linear Discriminant Analysis (LDA), it is assumed that each class has a Gaussian distribution. This assumption rarely holds in the real world problems. However, by removing this assumption, the problem become intractable and cannot be solved in analytic form. Quite recently, a group of evolutionary algorithms is introduced to solve this problem. These algorithms used a combination of fisher criterion and fuzzy membership function as their fitness function. It is widely acknowledged that computing the fitness function in an evolutionary algorithm needs to be very fast. Unfortunately, calculating fisher criterion for each chromosome in iterations of an evolutionary algorithm has a high computational cost. Furthermore it is known that the fuzzy membership function has an assumption of Gaussian distribution, thus using it as a fitness function will have same assumption issue that LDA had previously. In this paper, we suggest a new fisher criterion to incorporate in fitness function and show that it is theoretically faster than previous introduced criterion. In addition we theoretically prove the equality of proposed criterion. Next, in order to eliminate the Gaussian assumption, we offer a substitution for fuzzy membership fitness function which does not have Gaussian assumption. Moreover, the superior speed introduced fitness function theoretically investigated. At last, in order to confirm the effectiveness of proposed fitness functions, comprehensive experiments using twelve UCI repository dataset and two real world problems in face and object recognition is performed and the results is compared in both speed and accuracy.
Coverage and Lifetime Optimization by Self-Optimizing Sensor Networks

We propose an approach to self-optimizing wireless sensor networks (WSNs) which are able to find, in a fully distributed way, a solution to a coverage and lifetime optimization problem. The proposed approach is based on three components: (a) a multi-agent, social-like interpreted system, where the modeling of agents, discrete space, and time is provided by a 2-dimensional second-order cellular automata, (b) the interaction between agents is described in terms of the spatial prisoner’s dilemma game, and (c) a local evolutionary mechanism of competition between agents exists. Nodes of a WSN graph created for a given deployment of WSN in the monitored area are considered agents of a multi-agent system that collectively make decisions to turn on or turn off their batteries. Agents are controlled by cellular automata (CA)-based players participating in a variant of the spatial prisoner’s dilemma iterated game. We propose for players participating in this game a local payoff function that incorporates issues of area coverage and sensors energy spending. Rewards obtained by agent players depend not only on their personal decisions but also on their neighbor’s decisions. Agents act in such a way to maximize their own rewards, which results in achieving by them a solution corresponding to the Nash equilibrium point. We show that the system is self-optimizing, i.e., can optimize in a distributed way global criteria related to WSN and not known for agents, provide a balance between requested coverage and spending energy, and result in expanding the WSN lifetime. The solutions proposed by the multi-agent system fulfill the Pareto optimality principles, and the desired quality of solutions can be controlled by user-defined parameters. The proposed approach is validated by a number of experimental results.
Knowledge, Attitude, Practice, and Perceived Barriers for the Compliance of Standard Precautions among Medical and Nursing Students in Central India

Objectives: The aim of this study was to assess and compare (a) the knowledge, attitude, and practice of standard precautions (SPs), (b) the knowledge of post-exposure management, and (c) the perceived barriers underlying the noncompliance with SPs among future healthcare professionals (HCPs), i.e., students of medical and nursing courses in Central India. Setting and participants: A cross-sectional study was conducted in 2017–2018 among students of a medical and a nursing college using a pretested and modified questionnaire. Data were collected during 23 face-to-face sessions. Responses were scored according to standard guidelines of the Centers for Disease Control and Prevention and WHO, where each correct response was given a score of 1. Results: Among 600 participants, 51% of medical students and 75% of nursing students could not select the correct definition of SPs from the given options. Sixty-five percent of medical students (275/423) and 82% of nursing students (145/177) were unaware of the term post-exposure prophylaxis. Overall, knowledge about personal protective equipment and hazard symbols was poor (<25%). Furthermore, although theoretical knowledge about hand hygiene was good (510/600; 85%), its implementation was poor (<30%). Sixty-four percent of participants believed that the use of hand rub replaced the need for handwashing, even for visibly soiled hands. Some of the participants believed that the use of PPE might offend patients (16%). High workload and poor knowledge were other significant barriers underlying the noncompliance with SPs. Conclusions: A suboptimal translation of participants’ knowledge into practice is evident and signifies the presence of the know–do gap. Poor knowledge and inappropriate presumptions about the use of SPs discourage the practice of SPs. This results in increased healthcare-associated infections, increased treatment costs, and a suppressed social economy. The inclusion of a dedicated curriculum with repeated hands-on and practice-based training on SPs is suggested to minimize this know–do gap among future healthcare workers.
Synergistic markers based on inter-covariate association estimate treatment option with lower propensity to covariates

Background Propensity constitutes a common problem in identifying clinical outcome prediction model whose covariates include the treatment option, which is assumed to be randomly assigned but indeed dependent of other covariates in the training data. The genuine effect of treatment option cannot be elucidated under the influence of propensity. Existing approaches, such as matched-pairs study design, still cannot solve the problem for imbalanced or small datasets. Methods This work proposed an anti-propensity estimate of treatment option, which is generated by support vector classifier based on two synergistic markers that represent the lower and upper limits of inter-covariate association level. The algorithm for generating the synergistic markers was illustrated and the performance was evaluated on a public dataset of gene expression levels, which were obtained from surgically excised tumor samples in non-small cell lung cancer (NSCLC) patients where treatment option, i.e., adjuvant therapy or not, was known. Results Six covariates represented by the expression levels of ZNF217, ERCC3, PMS1, PIK3CB, BARD1, and MAPK1, were selected to generate two synergistic markers and classifier for estimating the adjuvant therapy option with substantially attenuated propensity. The estimation accuracy attained an area under the receiver-operating characteristics curve, 0.78, in the test set. Conclusions The proposed synergistic markers demonstrated a parsimonious and anti-propensity estimation of treatment option, which is ready for the further evaluation and application in the clinical outcome prediction model.
A framework for deriving analytic steady states of biochemical reaction networks

The long-term behaviors of biochemical systems are often described by their steady states. Deriving these states directly for complex networks arising from real-world applications, however, is often challenging. Recent work has consequently focused on network-based approaches. Specifically, biochemical reaction networks are transformed into weakly reversible and deficiency zero generalized networks, which allows the derivation of their analytic steady states. Identifying this transformation, however, can be challenging for large and complex networks. In this paper, we address this difficulty by breaking the complex network into smaller independent subnetworks and then transforming the subnetworks to derive the analytic steady states of each subnetwork. We show that stitching these solutions together leads to the analytic steady states of the original network. To facilitate this process, we develop a user-friendly and publicly available package, COMPILES (COMPutIng anaLytic stEady States). With COMPILES, we can easily test the presence of bistability of a CRISPRi toggle switch model, which was previously investigated via tremendous number of numerical simulations and within a limited range of parameters. Furthermore, COMPILES can be used to identify absolute concentration robustness (ACR), the property of a system that maintains the concentration of particular species at a steady state regardless of any initial concentrations. Specifically, our approach completely identifies all the species with and without ACR in a complex insulin model. Our method provides an effective approach to analyzing and understanding complex biochemical systems.
Comparison of Low and High Temperature Sintering for Processing of Bovine Bone as Block Grafts for Oral Use: A Biological and Mechanical In Vitro Study

Large oral bone defects require grafting of bone blocks rather than granules to give physically robust, biocompatible and osteoconductive regeneration. Bovine bone is widely accepted as a source of clinically appropriate xenograft material. However, the manufacturing process often results in both reduced mechanical strength and biological compatibility. The aim of this study was to assess bovine bone blocks at different sintering temperatures and measure the effects on mechanical properties and biocompatibility. Bone blocks were divided into four groups; Group 1: Control (Untreated); Group 2: Initial boil for 6 h; Group 3: Boil 6 h followed by sintering at 550 °C for 6 h; Group 4: Boil 6 h followed by sintering at 1100 °C for 6 h. Samples were assessed for their purity, crystallinity, mechanical strength, surface morphology, chemical composition, biocompatibility and clinical handling properties. Statistical analysis was performed using one-way ANOVA and post-hoc Tukey’s tests for normally distributed and Friedman test for abnormally distributed quantitative data from compression tests and PrestoBlue™ metabolic activity tests. The threshold for statistical significance was set at p < 0.05. The results showed that higher temperature sintering (Group 4) removed all organic material (0.02% organic components and 0.02% residual organic components remained) and increased crystallinity (95.33%) compared to Groups 1–3. All test groups (Group 2–4) showed decreased mechanical strength (MPa: 4.21 ± 1.97, 3.07 ± 1.21, 5.14 ± 1.86, respectively) compared with raw bone (Group 1) (MPa: 23.22 ± 5.24, p <0.05), with micro-cracks seen under SEM in Groups 3 and 4. Group 4 had the highest biocompatibility (p < 0.05) with osteoblasts as compared to Group 3 at all time points in vitro. Clinical handling tests indicated that Group 4 samples could better withstand drilling and screw placement but still demonstrated brittleness compared to Group 1. Hence, bovine bone blocks sintered at 1100 °C for 6 h resulted in highly pure bone with acceptable mechanical strength and clinical handling, suggesting it is a viable option as a block grafting material.