Goal Research Articles

The speech neuroprosthesis.

Loss of speech after paralysis is devastating, but circumventing motor-pathway injury by directly decoding speech from intact cortical activity has the potential to restore naturalcommunication and self-expression. Recent discoveries have defined how key features of speech production are facilitated by the coordinated activity of vocal-tract articulatory and motor-planning cortical representations. In this Review, we highlight such progress and how it has led to successful speech decoding, first in individuals implanted with intracranial electrodes for clinicalepilepsy monitoringand subsequently in individuals with paralysis as part ofearlyfeasibility clinical trials to restore speech. We discuss high-spatiotemporal-resolution neural interfaces and the adaptation of state-of-the-art speech computational algorithms that have driven rapidandsubstantial progress indecoding neural activity into text, audible speech, and facial movements. Although restoring natural speech is a long-term goal, speech neuroprostheses already have performance levels that surpass communication rates offered by current assistive-communication technology. Given this accelerated rate of progress in the field, we propose key evaluation metrics for speed and accuracy, among others, to help standardize across studies. We finish by highlighting several directions to more fully explore the multidimensional feature space of speech and language, which will continue to accelerate progress towards a clinically viable speech neuroprosthesis.

Production of biodiesel (isopropyl ester) from coconut oil by microwave assisted transesterification: parametric study and optimization

Biodiesel, a renewable fuel for diesel vehicle engines, has been commonly produced from transesterification process involving triglycerides from vegetable oil with alcohol. One of the most promising candidates for vegetable oil due to its abundance in Indonesia is coconut oil. However, the short carbon chain present in coconut oil necessitates the use of longer-chain alcohol types to adjust to the biodiesel carbon chain, such as isopropanol. Therefore, this research focused on producing biodiesel (isopropyl ester) from coconut oil using isopropanol and NaOH catalyst through a transesterification process. To enhance this process, microwave technology was utilized for its ability to lower the biodiesel production reaction time from the conventional one-hour timeframe to less than ten minutes, increase energy efficiency, and improve biodiesel quality. The primary objective was to investigate the impact of reaction time, catalyst concentration, and microwave power on the isopropyl ester yield. Further optimization was conducted using Response Surface Methodology (RSM) with Box-Behnken Design (BBD) to illustrate the model's effectiveness and applicability. Based on BBD optimization simulation, the optimal condition for producing isopropyl ester from coconut oil using microwave technology is a 1-minute reaction time, 0.2 wt.% NaOH catalyst concentration, and 443.9 W microwave power, maximizing the yield to 99.89%. This research highlights the potential of microwave assisted transesterification and the reliability of this innovative approach, contributing to the development of isopropyl ester production with enhanced quality that meets the specifications of the Indonesian National Standard (SNI).

Ibrutinib followed by ofatumumab consolidation in previously untreated patients with chronic lymphocytic leukemia (CLL): GELLC-7 trial from the Spanish group of CLL (GELLC)

BTK inhibitors have been concurrently administered with anti-CD20 monoclonal antibodies (mAbs) in chronic lymphocytic leukemia (CLL). However, the optimal regimen for combining these two drugs remains pending. This multi-center phase 2 study aimed to analyze whether consolidation with ofatumumab improved the response in patients with CLL receiving front-line treatment with ibrutinib. Patients received 12 cycles of ibrutinib monotherapy. Those who achieved CR after this induction were maintained on ibrutinib. Conversely, those who did not attain CR continued with ibrutinib in addition to a consolidation, which involved 7 doses of ofatumumab. The primary objective was the complete response (CR) rate at cycle 20. This study is registered within the EU Clinical Trials Register (EudraCT 2016-004937-26). Between September 8, 2017, and May 21, 2018, 84 patients (median age, 69 years) were included. After completion of 12 cycles of ibrutinib (n=80), 4 patients (5%) were in CR, 67 (84%) in partial response (PR), and 6 patients (7%) had a PR with lymphocytosis (PRL). After consolidation with ofatumumab, 20 patients improved the response from PR to CR and 6 patients with PRL obtained a PR. Seventy-one patients (85%) completed 20 cycles of treatment, with a CR rate of 24/71 (34%). According to the intention-to-treat analysis at cycle 20, the ORR was 69/84 (82.2%), with a CRR of 24/84 (28.6%). Progression-free survival and overall survival at 48-months were 89.9% (CI: 82.4-95.5) and 92.2% (CI: 85.3-97.1), respectively. These findings underscore the potential for a consolidation strategy in CLL, wherein the addition of a mAb in patients with low tumor burden might enhance the quality of the response. The study was funded by Janssen that also supplied ibrutinib, whereas ofatumumab was supplied by Novartis.

Ebselen: A Review on its Synthesis, Derivatives, Anticancer Efficacy and Utility in Combating SARS-COV-2.

Ebselen is a selenoorganic chiral compound with antioxidant properties comparable to glutathione peroxidase. It is also known as 2-phenyl-1,2-benzisoselenazol-3(2H)-one. In studies examining its numerous pharmacological activities, including antioxidant, anticancer, antiviral, and anti-Alzheimer's, ebselen has demonstrated promising results. This review's primary objective was to emphasize the numerous synthesis pathways of ebselen and their efficacy in fighting cancer. The data were collected from multiple sources, including Scopus, PubMed, Google Scholar, Web of Science, and Publons. The starting reagents for the synthesis of ebselen are 2-aminobenzoic acid and N-phenyl benzamide. It was discovered that ebselen has the ability to initiate apoptosis in malignant cells and prevent the formation of new cancer cells by scavenging free radicals. In addition, ebselen increases tumor cell susceptibility to apoptosis by inhibiting TNF-α mediated NF-jB activation. Ebselen can inhibit both doxorubicin and daunorubicin-induced cardiotoxicity. Allopurinol and ebselen administered orally can be used to suppress renal ototoxicity and nephrotoxicity. Due to excessive administration, diclofenac can induce malignancy of the gastrointestinal tract, which ebselen can effectively suppress. Recent research has demonstrated ebselen to inhibit viral function by binding to cysteine-containing catalytic domains of various viral proteases. It was discovered that ebselen could inhibit the catalytic dyad function of Mpro by forming an irreversible covalent bond between Se and Cys145, thereby altering protease function and inhibiting SARS-CoV-2. Ebselen may also inhibit the activation of endosomal NADPH oxidase of vascular endothelial cells, which is believed to be required for thrombotic complications in COVID-19. In this review, we have included various studies conducted on the anticancer effect of ebselen as well as its inhibition of SARS-CoV-2.

Novel Amide Functionalized Trifluoromethyl thieno[2,3-b]pyridine Derivatives: Anti-cancer Activity and Molecular Docking Studies

Abstract: Our primary research objective is to create and formulate small ring heterocycles with enhanced biological efficacy. Amide functionalized trifluoromethyl thieno[2,3-b]pyridine derivatives as a series were prepared starting from reaction between 1,3 di-ketone and thiocyanoacetamide and obtained pyridine 3. Compound 3 reacts with bromoethyl acetate and obtained compound 4, further compound 4 on reaction with diverse substituted aromatic and aliphatic amines to get amide derivatives 5a-d, 6a-d and 7a-h. All the final compounds evaluated for anti cancer activity against four human cancer cell lines such as ‘HeLa - Cervical cancer (CCL-2); COLO 205- Colon cancer (CCL- 222); HepG2 - Liver cancer (HB-8065); MCF7 - Breast cancer (HTB-22)’ and promising compounds 7d, 7e and 7f have been identified. For compounds 7d, 7e and 7f molecular docking interactions have been identified.

Energy management enhancement of a smart home supplied by renewable energy system

Solar energy is a reliable and eco-friendly solution for power outages in Karbala, Iraq. This study presents a smart grid technology model for energy management in electrical systems, optimizing power schemes and economic benefits through a unique spatial distribution approach in Iraq, with the primary objective of ensuring consistent base loads for smart homes while achieving other economic goals. The algorithm’s effectiveness was tested in three different scenarios. The energy was supplied by the national grid and battery bank-powered base loads. Meteorological data, including temperature and solar radiation, was gathered from a station in Karbala city for testing and evaluation. The study found that energy consumption decreased by 85% in April, with solar energy accounting for 37% of the total consumption. Smart homes saved 48% of energy, reducing reliance on the grid to 15%, as well as the reduction of energy consumption reached up to 47% and 60% in January and July, respectively, with solar energy estimated at 14% and 26% in those months.

Acceptability of artificial intelligence for cervical cancer screening in Dschang, Cameroon: a qualitative study on patient perspectives

BackgroundCervical cancer is the fourth most frequent cancer among women, with 90% of cervical cancer-related deaths occurring in low- and middle-income countries like Cameroon. Visual inspection with acetic acid is often used in low-resource settings to screen for cervical cancer; however, its accuracy can be limited. To address this issue, the Swiss Federal Institute of Technology Lausanne and the University Hospitals of Geneva are collaborating to develop an automated smartphone-based image classifier that serves as a computer aided diagnosis tool for cancerous lesions. The primary objective of this study is to explore the acceptability and perspectives of women in Dschang regarding the usage of a screening tool for cervical cancer relying on artificial intelligence. A secondary objective is to understand the preferred form and type of information women would like to receive regarding this artificial intelligence-based screening tool.MethodsA qualitative methodology was employed to gain better insight into the women’s perspectives. Participants, aged between 30 and 49 were invited from both rural and urban regions and semi-structured interviews using a pre-tested interview guide were conducted. The focus groups were divided on the basis of level of education, as well as HPV status. The interviews were audio-recorded, transcribed, and coded using the ATLAS.ti software.ResultsA total of 32 participants took part in the six focus groups, and 38% of participants had a primary level of education. The perspectives identified were classified using an adapted version of the Technology Acceptance Model. Key factors influencing the acceptability of artificial intelligence include privacy concerns, perceived usefulness, and trust in the competence of providers, accuracy of the tool as well as the potential negative impact of smartphones.ConclusionThe results suggest that an artificial intelligence-based screening tool for cervical cancer is mostly acceptable to the women in Dschang. By ensuring patient confidentiality and by providing clear explanations, acceptance can be fostered in the community and uptake of cervical cancer screening can be improved.Trial registrationEthical Cantonal Board of Geneva, Switzerland (CCER, N°2017–0110 and CER-amendment n°4) and Cameroonian National Ethics Committee for Human Health Research (N°2022/12/1518/CE/CNERSH/SP). NCT: 03757299.

Determining the extent and frequency of on-site monitoring: a bayesian risk-based approach

BackgroundOn-site monitoring is a crucial component of quality control in clinical trials. However, many cast doubt on its cost-effectiveness due to various issues, such as a lack of monitoring focus that could assist in prioritizing limited resources during a site visit. Consequently, an increasing number of trial sponsors are implementing a hybrid monitoring strategy that combines on-site monitoring with centralised monitoring. One of the primary objectives of centralised monitoring, as stated in the clinical trial guidelines, is to guide and adjust the extent and frequency of on-site monitoring. Quality tolerance limits (QTLs) introduced in ICH E6(R2) and thresholds proposed by TransCelerate Biopharma are two existing approaches for achieving this objective at the trial- and site-levels, respectively. The funnel plot, as another threshold-based site-level method, overcomes the limitation of TransCelerate’s method by adjusting thresholds flexibly based on site sizes. Nonetheless, both methods do not transparently explain the reason for choosing the thresholds that they used or whether their choices are optimal in any certain sense. Additionally, related Bayesian monitoring methods are also lacking.MethodsWe propose a simple, transparent, and user-friendly Bayesian-based risk boundary for determining the extent and frequency of on-site monitoring both at the trial- and site-levels. We developed a four-step approach, including: 1) establishing risk levels for key risk indicators (KRIs) along with their corresponding monitoring actions and estimates; 2) calculating the optimal risk boundaries; 3) comparing the outcomes of KRIs against the optimal risk boundaries; and 4) providing recommendations based on the comparison results. Our method can be used to identify the optimal risk boundaries within an established risk level range and is applicable to continuous, discrete, and time-to-event endpoints.ResultsWe evaluate the performance of the proposed risk boundaries via simulations that mimic various realistic clinical trial scenarios. The performance of the proposed risk boundaries is compared against the funnel plot using real clinical trial data. The results demonstrate the applicability and flexibility of the proposed method for clinical trial monitoring. Moreover, we identify key factors that affect the optimality and performance of the proposed risk boundaries, respectively.ConclusionGiven the aforementioned advantages of the proposed risk boundaries, we expect that they will benefit the clinical trial community at large, in particular in the realm of risk-based monitoring.

Traditional Chinese exercise in chronic obstructive pulmonary disease: An overview of systematic reviews

This study aims to critically reassess existing systematic reviews (SR) on Traditional Chinese Exercises (TCE) for treating Chronic Obstructive Pulmonary Disease (COPD). The primary objectives include synthesizing available evidence, evaluating the methodological quality of reviews and overall evidence, and providing comprehensive insights into the effectiveness of different TCE types in managing COPD. Sinomed, CNKI, VIP, Wanfang, PubMed, Cochrane Library, and Web of Science were searched from inception to April 2023 for SR literature on the treatment of COPD with TCE. The extracted data from the included SRs encompassed various aspects such as general information, study population, intervention measures, meta-analysis results, and conclusions. The methodological quality of the included SRs was assessed using the AMSTAR II tool. Additionally, the GRADE tool was used to determine the evidence level of outcome indicators. This study included 17 SRs and 4 types of TCE. The CCA was 0.041, indicating a slight overlap between the primary studies. Notably, one study was rated as low quality on the AMSTAR II scale, while the rest were classified as critically low quality. The results from the GRADE evaluation revealed 26 pieces of very low-quality evidence, 55 pieces of low-quality evidence, and 17 pieces of moderate-quality evidence. The moderate-quality evidence suggests that Liuzijue effectively improves TCM syndrome scores in patients with COPD. Additionally, low-quality evidence suggests that Liuzijue improves patients’ lung function (FEV1, FVC) and quality of life (CAT, MRC/mMRC). Similarly, low-quality evidence suggests that Baduanjin can improve patients’ lung function (FEV1%, FVC) and quality of life (SGRQ). Low-quality evidence also suggests that Health Qigong can significantly improve patients’ exercise endurance (6MWD). No SR reported TCE-related adverse reactions. TCE interventions are effective and safe in the treatment of COPD. Different types of TCE have varying effects on outcomes in COPD patients. However, these findings are limited by the generally low methodological and evidence quality of the included SRs. Therefore, it is strongly recommended to improve study designs to obtain higher-quality clinical evidence and to strictly follow SR protocols.

On the Impact of Lower Recall and Precision in Defect Prediction for Guiding Search-based Software Testing

Defect predictors, static bug detectors, and humans inspecting the code can propose locations in the program that are more likely to be buggy before they are discovered through testing. Automated test generators such as search-based software testing (SBST) techniques can use this information to direct their search for test cases to likely buggy code, thus speeding up the process of detecting existing bugs in those locations. Often the predictions given by these tools or humans are imprecise, which can misguide the SBST technique and may deteriorate its performance. In this article, we study the impact of imprecision in defect prediction on the bug detection effectiveness of SBST. Our study finds that the recall of the defect predictor, i.e., the proportion of correctly identified buggy code, has a significant impact on bug detection effectiveness of SBST with a large effect size. More precisely, the SBST technique detects 7.5 fewer bugs on average (out of 420 bugs) for every 5% decrements of the recall. However, the effect of precision, a measure for false alarms, is not of meaningful practical significance, as indicated by a very small effect size. In the context of combining defect prediction and SBST, our recommendation is to increase the recall of defect predictors as a primary objective and precision as a secondary objective. In our experiments, we find that 75% precision is as good as 100% precision. To account for the imprecision of defect predictors, in particular low recall values, SBST techniques should be designed to search for test cases that also cover the predicted non-buggy parts of the program, while prioritising the parts that have been predicted as buggy.

Beyond Translation: Exploring the Stigmatization of Rainbow Works Translation Under Frame Theory

ABSTRACT Drawing on Goffman’s frame theory, this study examines the attitudes of nine Chinese university teacher translators in translating rainbow works, ranging from hesitancy to resistance. The primary objective is to uncover the frames of stigmatization inherent in their negative attitudes toward rainbow works translation. The research clarifies the identities of perpetrators and victims in these frames leading to stigmatization. Findings indicate that various stigmatization events in rainbow works translation share a common feature—an unfavorable depiction of rainbow culture and related elements, encompassing the rainbow community, works, and translators. Perpetrators and victims vary across events, demonstrating diversity. The research interprets stigmatization in rainbow works translation at individual, institutional, and sociocultural levels. Providing a unique Chinese perspective, the study contributes to international understanding of stigmatization in a heteronormative society. It challenges traditional Chinese norms, advocates reevaluating identity labels for the rainbow community, and underscores the importance of addressing translators’ circumstances in translating rainbow works within specific societal contexts.

Association of Baseline Magnetic Resonance Imaging Prostate Imaging Reporting and Data System Score With Prostate Cancer Active Surveillance Early Biopsy Reclassification: Data From the Michigan Urological Surgery Improvement Collaborative (MUSIC).

The purpose of our study was to evaluate the association of baseline MRI Prostate Imaging Reporting and Data System (PI-RADS) score with biopsy reclassification in a multicenter active surveillance (AS) cohort. We identified men in the Michigan Urological Surgery Improvement Collaborative registry (46 hospital-based/academic/private practice urology groups) with National Comprehensive Cancer Network (NCCN) low-risk and favorable intermediate-risk prostate cancer who underwent MRI within 6 months before or after initial biopsy and enrolled in AS from June 2016 to January 2021. The primary objective was to determine the association of baseline MRI PI-RADS score (≥4 lesion) with reclassification to high-grade prostate cancer (≥grade group 3) on surveillance biopsy. Multivariable Cox proportional hazards regression models were constructed and adjusted for pathologic, MRI, and clinical/biopsy factors, with landmark time of 6 months from diagnostic biopsy. We included an interaction term between PI-RADS score and NCCN group in the Cox model. A total of 1491 men were included with median age 64 years (IQR: 59-69) with median follow-up 11.0 months (IQR: 6.0-23.0) after landmark. Baseline PI-RADS ≥ 4 lesion was associated with an increased hazard of biopsy reclassification (HR: 2.3 [95% CI: 1.6-3.2], P < .001), along with grade group 2 vs 1 (HR: 2.5 [95% CI: 1.7-3.7], P < .001), and increasing age (per 10 years; HR: 1.8 [95% CI: 1.4-2.4], P < .001). The interaction between NCCN risk group with MRI findings was not significant (P = .7). In this multicenter cohort study of real-world data, baseline MRI PI-RADS score was significantly associated with early biopsy reclassification in men undergoing AS with NCCN low- or favorable intermediate-risk prostate cancer.

Bidimensional Exploration of the warm-Temperature Ionised gaS (BETIS)

We present the Bidimensional Exploration of the warm-Temperature Ionised gaS (BETIS) project, designed for the spatial and spectral study of the diffuse ionised gas (DIG) in a selection of nearby spiral galaxies observed with the MUSE integral-field spectrograph. Our primary objective is to investigate the various ionisation mechanisms at play within the DIG. We analysed the distribution of high- and low-ionisation species in the optical spectra of the sample on a spatially resolved basis. We introduced a new methodology for spectroscopically defining the DIG, optimised for galaxies of different resolutions. Firstly, we employed an innovative adaptive binning technique on the observed datacube based on the spectroscopic signal-to-noise ratio (S/N) of the collisional [S II] line to increase the S/N of the rest of the lines including [O III], [O I], and He I. Subsequently, we created a DIG mask by eliminating the emissions associated with both bright and faint H II regions. We also examined the suitability of using Hα equivalent width (EWHα) as a proxy for defining the DIG and its associated ionisation regime. Notably, for EWHα &lt; 3 Å – the expected emission from hot low-mass evolved stars (HOLMES) – the measured value is contingent on the chosen population synthesis technique performed. Our analysis of the showcase sample reveals a consistent cumulative DIG fraction across all galaxies in the sample, averaging around 40%–70%. The average radial distribution of the [N II]/Hα, [S II]/Hα, [O I]/Hα, and [O III]/Hβ ratios are enhanced in the DIG regimes (up to 0.2 dex). It follows similar trends between the DIG regime and the H II regions, as well as the Hα surface brightness (ΣHα), indicating a correlation between the ionisation of these species in both the DIG and the H II regions. The DIG loci in typical diagnostic diagrams are found, in general, within the line ratios that correspond to photoionisation due to the star formation. There is a noticeable offset correspondent to ionisation due to fast shocks. However, an individual diagnosis performed for each galaxy reveals that all the DIG in these galaxies can be attributed to photoionisation from star formation. The offset is primarily due to the contribution of Seyfert galaxies in our sample, which is closely aligned with models of ionisation from fast shocks and galactic outflows, thus mimicking the DIG emission. Our results indicate that galaxies exhibiting active galactic nucleus (AGN) activity should be considered separately when conducting a general analysis of the DIG ionisation mechanisms, since this emission is indistinguishable from high-excitation DIG.

The Effects of mirror therapy in postural and kinesthetic rehabilitation on stance phase of gait in subacute stroke

Background: This study explored the effectiveness of mirror therapy in improving postural and kinesthetic rehabilitation during the stance phase of gait in subacute stroke patients. Given the crucial role of balance and functional recovery in enhancing mobility and overall quality of life in stroke survivors, the primary focus was on these aspects. Objective: The primary objective was to evaluate the impacts of mirror therapy on postural and kinesthetic rehabilitation during the stance phase of gait in subacute stroke patients. Methods: A randomized controlled trial was conducted over nine months in Rahim Yar Khan, involving both private and government hospitals. Sixty-four participants were randomly assigned to two groups: the Conventional+KTR group and the Mirror Therapy group, with 32 participants in each. Inclusion criteria required participants to have a single episode of hemiplegic subacute stroke diagnosed by a neurologist, inclusion of both ischemic and hemorrhagic stroke, and sufficient cognitive ability to follow instructions as indicated by a Mini-Mental State Examination (MMSE) score of 24 or higher. Mild spasticity in all joints of the affected limb was defined by a Modified Ashworth Scale score of less than 3. The intervention for the experimental group involved mirror therapy conducted four days a week for six weeks, supplemented by a home plan for the remaining three days. The control group received conventional therapy, including proprioceptive neuromuscular facilitation (PNF) and electrical interventions, also for four days a week, with a home plan for the remaining days. Key outcome measures were the Berg Balance Scale (BBS) for balance and the Fugl-Meyer Assessment for functional recovery. Data were analyzed using SPSS Version 25, with significance set at p&lt;0.05. Results: The Mirror Therapy group showed significantly greater improvements in balance scores, with a mean BBS of 40.31 at week 6 compared to 36.78 in the Conventional+KTR group (p&lt;0.001). Functional recovery was more pronounced in the Conventional+KTR group, which had a mean Fugl-Meyer Assessment score of 35.63 at week 6 compared to 30.50 in the Mirror Therapy group (p&lt;0.001). Gender distribution was similar across both groups, with the Conventional+KTR group consisting of 21.9% males and 78.1% females, and the Mirror Therapy group having 18.8% males and 81.3% females. Conclusion: Mirror therapy significantly enhances postural and kinesthetic rehabilitation in subacute stroke patients, particularly in improving balance more effectively than Conventional+KTR therapy. Conversely, Conventional+KTR therapy showed better results in functional recovery. These findings suggest that mirror therapy can be a valuable addition to stroke rehabilitation programs, offering a potential avenue for improved patient outcomes. Keywords: Mirror Therapy, Subacute Stroke Rehabilitation, Gait Improvement, Postural Awareness, Kinesthetic Awareness, Berg Balance Scale, Fugl-Meyer Assessment, Randomized Controlled Trial, Stroke Recovery, Balance Rehabilitation.

Analgesic Effects of Intraperitoneal Lidocaine in Adults Undergoing Surgery: A Systematic Review and Meta-Analysis with Trial Sequential Analysis.

The administration of local anaesthesia in intraperitoneal space as part of the multi-modal analgesic regimen has shown to be effective in reducing postoperative pain. Recent studies demonstrated that intraperitoneal lidocaine may provide analgesic effects. Primary objective was to determine the impact of intraperitoneal lidocaine on postoperative pain scores at rest. We carried out a systematic review and meta-analysis according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Databases of MEDLINE, EMBASE, and CENTRAL were searched from their inception date until May 2023. Randomized clinical trials (RCT) comparing intraperitoneal lidocaine and placebo in adults undergoing surgery were included. Our systematic review included 24 RCTs (n = 1,824). The intraperitoneal lidocaine group was significantly associated with lower postoperative pain scores at rest (MD: -0.87, 95% CI: -1.04 to -0.69) and at movement (MD: -0.50, 95% Cl: -0.93 to -0.08) among adult patients after surgery. Its administration also significantly decreased morphine consumption (MD: -6.42 mg, 95% Cl: -11.56 to -1.27), lowered the incidence of needing analgesia (OR: 0.22, 95% Cl: 0.14 to 0.35). Intraperitoneal lidocaine statistically reduced time to resume regular diet (MD: 0.16 days; 95% Cl: -0.31 to -0.01), and lowered postoperative incidence of nausea and vomiting (OR: 0.54, 95% Cl: 0.39 to 0.75). In this review, our findings should be interpreted with caution. Future studies are warranted to determine the optimal dose of administering intraperitoneal lidocaine among adult patients undergoing surgery.

The Dark Side of Family Embeddedness: Family Firms Engagement in Private-Sector Corruption

This research analyzes how family embeddedness affects the decision of owners in charge of small entrepreneurial family firms operating in an emerging country to participate in private-sector corruption. Prior research has typically assumed that those in charge of family firms choose to participate in corruption to receive an immediate economic benefit. We challenge this assumption and argue that family influences the decision of the owner of small entrepreneurial family firms to participate in private-sector corruption driven by the pursuit of both short-term economic (profit maximization) and long-term non-economic goals, including attaining upper social class status (even if this decreases economic gains) for the family unit. We further find that in the context of an emerging market, trusted intermediaries can be seen as family members by the owners in charge of small entrepreneurial family firms and can influence them to participate in illicit activities. We also contend that those in charge of small entrepreneurial family businesses manage participation in private-sector corruption by dissociating and framing means.

Orientation-dependent multi-spall performance of monocrystalline NiTi alloys under shock compression

The primary objective of this work was committed to large-scale non-equilibrium molecular dynamics modeling for the investigation on multiple spall performance, microstructural evolutions, and melting state of NiTi alloys along three typical crystal orientations. We discovered that there was a single-wave structure present in the [100] orientation, whereas elastic-plastic two-wave structures were found in [110] and [111], exhibiting a significant anisotropy in elastic-plastic wave velocity. Compared to [110] and [111] orientations, multi-spallation was more likely to be generated in the [100] direction. During accumulative dynamic damage, there was also a strong sensitivity of void evolution to orientation. For [100], voids tended to be densely distributed in the material and exhibited a strip-shaped manner. In contrast, a more scattered void distribution was observed for the other two orientations, showing a flaky pattern. Interestingly, dislocations in the spall region were almost annihilated before approaching void nucleation. According to void statistics, the peak number of voids, void nucleation rate, and spall region size were identified to be in a good uniformity along [110], [100], and [111]. For all the cases, the samples experienced partial melting in the released state and were followed by a recovery of structural order degree. However, there was an insignificant anisotropy in the melting state for each crystal orientation during multi-spallation.

Modelling the Growth of Listeria monocytogenes on Fresh-Cut Cucumbers at Various Storage Temperatures

The primary objective of this study was to investigate the behavior of Listeria monocytogenes (L. monocytogenes) on fresh-cut cucumbers. Fresh-cut cucumber samples were inoculated with a mixture of six strains of L. monocytogenes. The inoculated samples were stored at 5, 10, 15, 20, 25, 30, and 35 °C. The results demonstrated that L. monocytogenes was able to grow on fresh-cut cucumbers at all the evaluated temperatures, although its growth decreased but was not inhibited at 5 °C. An extreme storage temperature of 35 °C considerably reduced the lag time. L. monocytogenes growth on fresh-cut cucumbers was controlled for several days by storage at a low temperature, mainly at 5 °C. Thus, this product should only be stored at low temperatures. The growth process was fitted by the Baranyi model, with the specific growth rates equally well-fitted to the Ratkowsky square-root model. The R-square and mean square error values for the corresponding Ratkowsky square-root models were 0.97 (R2 &gt; 0.95) and 0.02, respectively. The Baranyi and Ratkowsky square-root models exhibited good relevancy. The predictive models developed in this study can be used to estimate the risk assessment of L. monocytogenes on fresh-cut cucumber.

The Influence of Asset Structure and Capital Structure on Return on Assets

In a competitive business environment, PT. AirAsia Indonesia Tbk. faces challenges in enhancing financial performance through efficient asset structure management and capital structure. This study examines the impact of asset structure and capital structure on operational efficiency and profit performance of PT. AirAsia Indonesia Tbk. within a highly competitive business setting. The primary objective of this study is to understand the dynamics between financial structure, debt management, and operational efficiency in relation to the company's financial performance. Utilizing financial data from the years 2015 to 2023, this research applies path analysis to evaluate the influence of asset structure and capital structure on efficiency ratios and their subsequent impact on the company's profit performance. This study concludes that although there is a significant relationship between asset structure and capital structure with operational efficiency ratios, this relationship does not significantly affect the company's profit performance. These findings provide important insights for the management of PT. AirAsia Indonesia Tbk. in optimizing asset structure and capital structure to improve operational efficiency without a significant impact on enhancing profit performance.

A Systematic Survey of Machine Learning and Deep Learning Models Used in Industrial Internet of Things Security

IIoT “Industrial Internet of Things” refers to a subset of Internet of Things technology designed for industrial processes and industrial environments. IIoT aims to make manufacturing facilities, energy systems, transportation networks, and other industrial systems smarter, more efficient and connected. IIoT aims to reduce costs, increase productivity, and support more sustainable operations by making industrial processes more efficient. In this context, the use of IIoT is increasing in production, energy, healthcare, transportation, and other sectors. IoT has become one of the fastest-growing and expanding areas in the history of information technology. Billions of devices communicate with the Internet of Things with almost no human intervention. IIoT consists of sophisticated analysis and processing structures that handle data generated by internet-connected machines. IIoT devices vary from sensors to complex industrial robots. Security measures such as patch management, access control, network monitoring, authentication, service isolation, encryption, unauthorized entry detection, and application security are implemented for IIoT networks and devices. However, these methods inherently contain security vulnerabilities. As deep learning (DL) and machine learning (ML) models have significantly advanced in recent years, they have also begun to be employed in advanced security methods for IoT systems. The primary objective of this systematic survey is to address research questions by discussing the advantages and disadvantages of DL and ML algorithms used in IoT security. The purpose and details of the models, dataset characteristics, performance measures, and approaches they are compared to are covered. In the final section, the shortcomings of the reviewed manuscripts are identified, and open issues in the literature are discussed.