Miracle-dz/UniFAR-FTUs huggingface dataset:
OPTIMIZATION AND CHARACTERIZATION OF MELOXICAM ORODISPERSIBLE TABLETS USING MIXED HYDROTROPY FOR ENHANCED WATER SOLUBILITY

Introduction: In order to attain rapid discharge in saliva and enhanced absorption, drug was incorporated in a fast-dissolving dosage form (ODTs) as a solid dispersion. In this present work ODTs of Meloxicam were prepared by sublimation techniques where different subliming agents were used with super disintegrant. Materials and Methods: Hydrotropic solid dispersions were prepared using different ratios (1:2, 1:4 and 1:6) of drug and hydrotropic blends (Niacinamide, Anhy. Sodium citrate, Sodium Salicylate and Sodium benzoate). Best hydrotropic solid dispersion was selected to prepare ODTs comprising of croscarmellose sodium and camphor in different concentration along with other pharmaceutical excipients. From the primary trial batches, T3 was selected for optimization experimental designs due to lowest disintegration time and highest in vitro drug release. Secondary batches (F1-F9) were prepared by using 32 full factorial design with different concentration of croscarmellose sodium (12, 14 and 16 mg) and camphor (8, 10 and 12 mg) as two independent variables while disintegration time and percent friability were considered as two dependent response variables. These formulations were subjected to study of various post compression evaluation parameters like hardness, thickness, friability, weight variation, disintegration time (25-117 sec) and in-vitro drug release (99.09%). Result and Discussion: Equilibrium solubility studies were reported that by utilizing hydrotropy, the solubility of Meloxicam got enhanced from 20.5 to 140.96 times as compared to its aqueous solubility. The desirability fraction was used to optimize the response variables for specific targets, i.e., minimum disintegration time and maximum dissolution, and the responses obtained were consistent for experimental values.
Safety of Level 4 Autonomous Vehicle: Still Human in the Loop

When Autonomous vehicles have come into the limelight both in the field of practical use and in the research domain, the continuous complexity of shared decision-making, liability, and ethics in a human-autonomy team is still finding ways to be resolved. Especially in level 4 autonomous vehicles, when almost everything is to be done by the autonomous system, the role of humans needs to be more structured. In this paper, we discuss the safety concern of a level 4 autonomous vehicle, keeping the human users in focus. We identify the critical safety concerns that can occur in a level 4 autonomous vehicle due to the autonomous system's error and how humans in and out of the loop can play a role there. We have three major topics discussed in this paper regarding the safety of level 4 autonomous vehicles: 1) identification of major safety issues of a level 4 autonomous vehicle, where we discuss the safety issue that can arise and whether the human user's invention can prevent the hazard, 2) discussion of the factors which needs to be considered to build an efficient Human-Machine Interface, through which the human user will be in the loop of the operation of the autonomous system and can play a crucial role to prevent potential safety hazard caused by the autonomous system error, 3) potential use of brain-machine interface technology to provide more robustness to the human-autonomy teaming in an autonomous vehicle context.
Cardio-Metabolic Health of Offspring Exposed in Utero to Human Immuno-Deficiency Virus and Anti-Retroviral Treatment: A Systematic Review

Simple Summary Although the use of antiretroviral treatment (ART) is effective in reducing the risk of HIV transmission to the foetus, there are concerns of possible adverse effects of in utero exposure on offspring’s cardio-metabolic health. This paper systematically reviewed the effects of HIV/ART exposure during pregnancy on the cardio-metabolic health of offspring. Reports from 35 eligible studies showed that HIV-exposed uninfected (HEU) children’s cardio-metabolic health was negatively impacted by in utero exposure to ART. A few studies showed direct cardiometabolic risk factors including increased blood pressure and lipids, reduced insulin, oxidative stress, cardiac damage and vascular and myocardial dysfunction among HEU children compared to their HIV-unexposed uninfected (HUU) children while most studies reported indirect cardiovascular risk factors including reduced head circumference, low birth weight, and altered mitochondrial content in HEU children. These findings suggest that in utero exposure of ART may affect foetal health predisposing them to cardiometabolic diseases later in life. Abstract Background: Antiretroviral treatment (ART) use during pregnancy continues to rise as it is known to decrease the likelihood of HIV transmission from mother to child. However, it is still unknown whether foetal exposure to (ART) may affect the foetal environment, predisposing the offspring to cardiometabolic risk. Therefore, the aim of this study was to systematically review the cardio-metabolic effects of in utero exposure to HIV/ART on offspring. Methods: We carried out a systematic review and obtained literature from the Google scholar, PubMed, ProQuest, Web of Science, and Scopus databases. Two independent reviewers evaluated the titles, abstracts, and full-length English contents. Data from the eligible studies were included. Results: The search yielded 7596 records. After assessing all of these records, 35 of the full-length articles were included in this systematic review. Several studies showed that low birth weight, small head circumference, and altered mitochondrial content were more common among HIV-exposed uninfected (HEU) children compared to HIV-unexposed uninfected children (HUU). A few studies demonstrated elevated triglyceride levels, lower levels of insulin, and increased blood pressure, oxidative stress, vascular dysfunction, cardiac damage, and myocardial dysfunction among HEU children compared with HUU children. Conclusion: Most findings showed that there were cardio-metabolic health risk factors among HEU children, indicating that maternal exposure to HIV and ART may negatively affect foetal health, which may lead to cardio-metabolic morbidity later in life.
Cereal-legume intercropping: a smart review using topic modelling

Introduction Over the last decade, there has been a growing interest in cereal-legume intercropping for sustainable agriculture. As a result numerous papers, including reviews, focus on this topic. Screening this large amount of papers, to identify knowledge gaps and future research opportunities, manually, would be a complex and time consuming task. Materials and methods Bibliometric analysis combined with text mining and topic modelling, to automatically find topics and to derive a representation of intercropping papers as a potential solution to reduce the workload was tested. Both common (e.g. wheat and soybean) as well as underutilized crops (e.g. buckwheat, lupin, triticale) were the focus of this study. The corpus used for the analysis was retrieved from Web of Science and Scopus on 5 th September 2022 and consisted of 4,732 papers. Results The number of papers on cereal-legume intercropping increased in recent years, with most studies being located in China. Literature mainly dealt with the cereals maize and wheat and the legume soybean whereas buckwheat and lupin received little attention from academic researchers. These underutilized crops are certainly interesting to be used as intercropping partners, however, additional research on optimization of management and cultivar’s choice is important. Yield and nitrogen fixation are the most commonly studied traits in cereal-legume intercropping. Last decade, there is an increasing interest in climate resilience, sustainability and biodiversity. Also the term “ecosystem services” came into play, but still with a low frequency. The regulating services and provisioning services seem to be the most studied, in contrast terms related to potential cultural services were not encountered. Discussion In conclusion, based on this review several research opportunities were identified. Minor crops like lupin and buckwheat need to be evaluated for their role as intercropping partners. The interaction between species based on e.g. root exudates needs to be further unraveled. Also diseases, pests and weeds in relation to intercropping deserve more attention and finally more in-depth research on the additional benefits/ecosystem services associated with intercropping systems is necessary.
Effects of the LPCVD Gate Dielectric Deposition Temperature on GaN MOSFET Channels and the Root Causes at the SiO2-GaN-Interface

MOSFETs have been fabricated on 150 mm heteroepitaxial gallium nitride (GaN)-on-Si wafers. This work focuses on the significant impact of the gate dielectric deposition temperature and investigates the resulting transistor channel characteristics, the gate dielectric robustness, and the underlying physical mechanisms. It is shown that varying the SiO2 gate dielectric deposition temperature below and above the GaN decomposition temperature resulted in a channel mobility of 17–55 cm2/Vs at threshold voltages of 8.0 to −3.2 V, respectively. Gate dielectric robustness and reliability studies demonstrated that oxide charging effects and lifetime also depend on the deposition temperature. In addition to the electrical measurements, secondary ion mass spectrometry (SIMS) and transmission electron microscopy (TEM) are used to identify root causes. It is found that various defect types, i.e., chargeable interface states, fixed oxide charges, diffusion of foreign atoms, vacancies, and surface roughness depend on the deposition temperature. In particular, SIMS measurements revealed a temperature-dependent diffusion of potential n-type dopants, originating from the SiO2 deposition, into the p-type channel region. As further tuning parameter of threshold voltage and channel mobility, the influence of the magnesium doping concentration of the p-body layer is investigated.
Research on deep brain stimulation in depression

Deep Brain Stimulation (DBS), as a neural modulation technique, has been widely used during the treatment of depression. The aim of this review is exploring the role of DBS in depression treatment and focuses on the combination of DBS and Brain-Computer Interface (BCI) applications. Firstly, we review the pathophysiological features of depression and the limitations of traditional treatment methods. Subsequently, we introduce the principles of DBS and its application in patients with depression. DBS modulates neural circuit activity by electrically stimulating specific brain regions such as the Anterior Cingulate Cortex (ACC) and Subgenual Cingulate Cortex (SGC), leading to an improvement in depressive symptoms. Next, we discuss the development and application of BCI technology in the field of neural modulation. BCI, as a technology that directly translates brain signals into control of external devices, offers new possibilities for DBS treatment. By combining BCI with DBS, individualized monitoring of brain electrical activity and closed-loop modulation can be achieved, enhancing the precision and effectiveness of treatment. While current research is still in its early stages, promising results have been obtained, providing guidance for future clinical applications. Lastly, we discuss the prospects of combining DBS and BCI for the treatment of depression and propose further research directions and challenges. The development of this integrated treatment approach holds promise for providing more effective and personalized treatment options for patients with depression.
Feasibility of Measuring Brake-Wear Particle Emissions from a Regenerative-Friction Brake Coordination System via Dynamometer Testing

Emissions of brake-wear particles are commonly associated with vehicular traffic. We investigated the feasibility of quantifying brake-wear particle emissions under realistic vehicle driving and braking conditions with a currently used regenerative friction brake coordination system. We used a braking system installed in commercially available plug-in hybrid electric vehicles and found that it reduced emissions by 85% for PM10, 78% for PM2.5, and 87% for particle numbers (PNs) compared with the system installed in vehicles with internal combustion engines. Brake friction work showed a linear relationship with PM10 and PM2.5. Nanoparticle PM emissions tended to increase slightly with regenerative braking but did not contribute significantly to the overall PM percentage. The emission events of high concentrations of nuclei-mode particles (<20 nm in diameter) in electric vehicle brake assemblies designed for regenerative braking use under high-temperature, high-load braking conditions with full-friction brakes. The nuclei-mode particles amplified the PN emissions and led to high variability. In strict regulatory certification tests where measurement reproducibility and stability are required, it is appropriate to measure PNs under brake conditions appropriate for the actual use of electric vehicles rather than under full-friction brake conditions or to remove particle measurements smaller than 20 nm.
Research on Design Method of Low Voltage ESD Protection for Chips based on CMOS Technology

As integrated circuit technology continuously evolves towards nanometre scales, the susceptibility of chips to Electrostatic Discharge (ESD) under low voltage conditions has significantly increased, posing greater challenges for ESD protection design. Traditionally, ESD protection strategies have centred on high-voltage applications, employing complex and cumbersome circuits and components to enhance tolerance. However, these methods often underperform in low-voltage CMOS processes due to excessive leakage currents, increased chip area, and an inability to meet the requirements of low power consumption and high integration of devices. This study introduces a novel universal framework for low-voltage ESD protection design methods applicable to various CMOS technology standards. The framework not only compares the merits and demerits of existing mainstream ESD protection devices, ESD testing methodologies, and ESD protection networks, but also introduces an innovative analytical paradigm to holistically consider the interplay among these three facets within low-voltage ESD protection design, thereby offering fresh insights for theoretical and practical research. This universal architecture, while ensuring compatibility, also demonstrates exceptional efficiency, which represents it can be easily and swiftly applicable to different CMOS technology standards.
The Mediating Role of Attitude Towards Intentional Buying of Counterfeit Goods: An Indian Consumer’s Perspective

The current study offers a conceptual framework for how consumer attitude for buying the counterfeit goods may mediates the relationship between consumer perceptions and their buying intentions to acquire the counterfeit goods in India. A hypothetical model is being proposed and validated through survey questionnaire. An overall sample size of 960 respondents were being selected from the different counterfeit markets of Delhi (India). To capture the true behavior of shoppers in the retail environment, face-to-face interviews were conducted utilizing the mall-intercept approach. The mediation model is validated through SPSS and PROCESS macro. According to the results, consumers' view of buying counterfeit goods has a favorable impact on their purchase intentions, and this effect is entirely mediated by customers' perception of buying counterfeit goods in India. This study is admissible to the present marketing environment because it offers brand makers and marketers insightful information that they can use to create strategies and regulations that will effectively sway customers' decisions to buy counterfeit goods in India.
Ground Reaction Forces, Asymmetries and Performance of Change of Direction Tasks in Youth Elite Female Basketball Players

The magnitude and direction of inter-limb asymmetries in a change of direction (COD) have increased interest in scientific research in recent years. This present study aimed to investigate the magnitude of asymmetries in an elite youth female basketball sample (n = 18, age = 17.79 ± 0.67 y) and determine its directionality using force platform technology. Participants performed 70° and 180° COD tests analyzing the following variables: time, ground contact time (GCT) and ground reaction forces (GRF) along the anterior–posterior, mediolateral, and vertical axes. Inter-limb asymmetries were evident in both COD tests, with substantial differences observed between limbs (p < 0.01). The asymmetry values ranged from 3.02% to 24.31% in COD 180° and from 1.99% to 21.70% in COD 70°, with anterior–posterior GRF consistently exhibiting the highest asymmetry magnitude. Additionally, the directionality exhibited variability between the tests, indicating poor agreement and suggesting the independent directionality of asymmetries across tasks. Moreover, players required more time to complete the COD 180°, the GCT was noticeably longer for the COD 180° than for the COD 70°, and GRF varied across the axis, suggesting that players adapt uniquely to the specific demands of each task. The utilization of force platforms presents a comprehensive approach to assess asymmetries and COD variables performance variables which are “angle-dependent”, which could have important implications for COD screening and effective training interventions.
Secure and Efficient Similarity Retrieval in Cloud Computing Based on Homomorphic Encryption

With the rapid development of cloud computing, massive amounts of data are uploaded to cloud servers for storage. For privacy protection, sensitive data should be encrypted before outsourcing, and ciphertext retrieval technologies based on similarity come into being. In cloud computing with massive data, the efficiency and accuracy of retrieval are crucial. However, most of the current similarity retrieval schemes do not perform well in these two aspects. Therefore, we propose SESR scheme, a secure and efficient similarity retrieval scheme based on homomorphic encryption. Firstly, we use Hamming distance to calculate the similarity between the feature vector of the data and query vector from the data user. Secondly, the homomorphic encryption algorithm is used to encrypt data to protect data privacy. Furthermore, we creatively design a BK-KD tree structure that hierarchically implements similarity search and fine-grained access control, thereby speeding up the retrieval efficiency. In addition, we design a two-cloud-server cooperative retrieval model and a message authentication scheme, which ensure access pattern privacy security and the integrity of the transmitted data simultaneously. We also propose an improved SESR scheme. In this scheme, we use Simhash algorithm to generate feature vectors and query vectors, which reduces storage overhead. Finally, the security of SESR is formally proved and the simulation results show the efficiency and accuracy of the retrieval scheme.
Active walking in broiler chickens: a flagship for good welfare, a goal for smart farming and a practical starting point for automated welfare recognition

Automated assessment of broiler chicken welfare poses particular problems due to the large numbers of birds involved and the variety of different welfare measures that have been proposed. Active (sustained, defect-free) walking is both a universally agreed measure of bird health and a behavior that can be recognized by existing technology. This makes active walking an ideal starting point for automated assessment of chicken welfare at both individual and flock level.
Squashing Resource Exhaustion Bugs with Black-Box Fuzzing and Reinforcement Learning

For a software system to be reliable, it must manage its resources properly. Failure to do so will result in unreliable behaviour: an application that leaks memory will eventually crash, a packet source that overloads a queue may cause other systems to fail, a process that consumes too many CPU cycles will degrade the performance of other processes and so on. Resource leaks or resource exhaustion are difficult to discover during testing as it may happen slowly over a long time. One approach for discovering issues with reliability, security and robustness is fuzzing (short for fuzz testing). Fuzzing can take many forms, depending on what type of system is to be tested and what kinds of bugs one is after. Black-box fuzzing is arguably the most flexible approach to fuzzing. Unfortunately, it suffers from a low efficiency that makes it slow at finding bugs such as resource leaks. In this paper we explore the topic of black-box fuzzing by modeling it as a multi-armed bandit problem, an important subclass of the general reinforcement learning problem. We believe that by utilizing a reinforcement learning framework, black-box fuzzing can be better understood and attention can be drawn to the field, which deserves to be studied more. We also implement a fuzzer according to our model and evaluate it against a toy implementation of a simple protocol with a known resource leak. Lastly, we apply our fuzzer in a real-world case study against two widely distributed implementations of the Link Layer Discovery Protocol (LLDP), a key component in critical infrastructure applications such as network management and network automation. Our results show that our fuzzer gradually learns how to effectively trigger the resource leak in the toy implementation, thereby speeding up the bug discovery process. In the case study, the fuzzer struggles to learn from the observations it makes about the test target. We believe this to be because of excessive delays between the actions the fuzzer takes during testing and their corresponding effects. Despite this, our fuzzer still manages to find one resource leak in each of the two LLDP implementations, one of which was previously unknown. With this paper, we have taken the first steps towards a better understanding of black-box fuzzing and that a new generation of smart and highly efficient black-box fuzzers is within reach.
Does Intellectual Capital Efficiency Matter for Firms' Investment Efficiency?

The determination of investment expenditures' compatibility with growth opportunities always remains a challenge for organizations. However, the efficient utilization of resources of firms may help them to overcome the challenge of over and under-investment. The present study examines the direct and indirect effect of intellectual capital efficiency (ICE) on firms' investment efficiency (IE) where the channel of indirect effect is the financial constraint (FC) faced by firms. For this, we developed a panel of 174 firms belonging to Pakistan from 2016 to 2020. In the first stage, we measure investment efficiency as a trichotomous variable under the categories of firms with over-investment, under-investment, and optimal (efficient) investment. In the second stage, we converted our panel data into cross-sectional data by taking an average of all variables and then used the multinomial logistic regression model to estimate the direct and indirect effect of intellectual capital efficiency on firms' investment efficiency. The findings of the present research reveal that although intellectual capital efficiency, measured by the E-VAIC model, does not have a direct effect on investment efficiency, it affects investment efficiency indirectly through the channel of financial constraint measured by Z-Score. Therefore, firms should work on the enhancement of the efficiency of their intellectual capital to avoid the problem of inefficient investment.