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Doubtless, Machine Translation has affected translation as a process and a product. This study tests MT's effectiveness in translating proverbs between English and Arabic. It investigates one important CAT tool device. It aims to attest which MT will be more communicative, semantic or literal giving target equivalent and clarifying the error type the MT would make. To achieve these aims, thirty proverbs, half Arabic and half English, have been randomly selected, taken from The Dictionary of Common English Proverbs Translated and Explained written by Attia (2004) and then translated using five different online MTs: Google, Reverso, Yandex, Systran, and Bing. As Alabbasi (2015) suggested, the researcher adopted Newmark's (1988) Taxonomy of translation methods, selecting three major divisions that include the other types in one way or another viz. Literal, Semantic and Communicative. Analyzing data, Kruskal-Wallis Test and Chi-square were used as well as descriptive statistics. It is found that the most translation method MT produced when faced with a proverb is the literal, semantic and communicative respectively. Bing is the most effective MT providing communicative proverbial equivalents. Bing and Google, in the same rank, provide semantic equivalents. Furthermore, the least effective MT among the five is Yandex. MT errors diverge between missing the implied meaning, weakly structured translations, wrong synonyms and meaning distorting.

Allusion is one of the culture-bound expressions that need careful consideration while translating. Machine translation (MT) and human translators (HTs) encounter difficulties in dealing with them. This study compares Translation Quality (TQ) of MT and Artificial Intelligence (AI) to HTs utilizing MTPE focusing on identifying the MTPE skills to keep HT in favor of MT and AI. A quantitative and qualitative mixed method was adopted using a test of 30-item in-context English-to-Arabic allusions translated by Google Translate and ChatGPT and then given to a random sample of 40 HTs. The TQ of AI, MT and HT target texts were assessed following O'Brien's (2012) model. The participants wrote reports on MTPE skills and were involved in a focus group discussion to determine the MTPE skills used. One-Sample t-Test, One-Way ANOVA and POST HOC Test were used. Results show HTs utilizing MTPE are of Moderate Quality (60%), and MT and AI-based translations are of Low Quality (44.44% & 42.22%). HTs employ some MTPE skills and strategies that resulted in statistically significant differences between HTs of allusions compared to MT and AI in favor of HTs. The study recommends enhancing MTPE skills among translation students and implementing training for further developing translators.

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, and poorer data transmission to the Base station (BS) when it was deployed for a longer period of time. In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol (HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. All these strategies are aiming at reducing energy consumption and extend the life of the network. Results show that the proposed routing scheme outperforms two existing ones in terms of stability period, throughputs, residual energy, and the lifetime of the network.

Objectives. To determine factors associated with mortality among confirmed Lassa fever cases. Methods. We reviewed line lists and clinical records of laboratory-confirmed cases of Lassa fever during the 2016 outbreak in Nigeria to determine factors associated with mortality. We activated an incident command system to coordinate response. Results. We documented 47 cases, 28 of whom died (case fatality rate [CFR] = 59.6%; mean age 31.4 years; SD = ±18.4 years). The youngest and the oldest were the most likely to die, with 100% mortality in those aged 5 years or younger and those aged 55 years or older. Patients who commenced ribavirin were more likely to survive (odds ratio [OR] = 0.1; 95% confidence interval [CI] = 0.03, 0.50). Fatality rates went from 100% (wave 1) through 69% (wave 2) to 31% (wave 3; χ 2 for linear trend: P < .01). Patients admitted to a health care center before incident command system activation were more likely to die (OR = 4.4; 95% CI = 1.1, 17.6). The only pregnant patient in the study died postpartum. Conclusions. Effective, coordinated response reduces mortality from public health events. Attention to vulnerable groups during disasters is essential. Public Health Implications. Activating an incident command system improves the outcome of disasters in resource-constrained settings.

Data science explores the use of big data to gain deeper insights and generate new knowledge and innovations which can lead to economic growth and sustainable development. However, setting up data science research comes with challenges. How we engage stakeholders is a major factor that determines success. This Commentary highlights important considerations for stakeholder engagement based on the experiences of investigators in a data science for health discovery project underway in Nigeria and South Africa. The perspectives presented will guide implementation in this relatively new but rapidly growing research domain.

It is common to detect a gap between the apical portion of the post and the most coronal part of gutta-percha in a root canal during post and core treatment in endodontically treated teeth. It may compromise the seal that gutta-percha material provides in the root canal filling, leading to apical leakage, which is often thought to be one of the most common causes for failure of endodontic treatment. The prevention of apical leakage to achieve a complete apical seal and its effect on periapical health of endodontically treated teeth of post and core in long term clinical research remains unanswered. Post and core treatment were provided to 100 patients by undergraduate students in the year 2016–2017. A total of 70 patients in all were called back to the Prosthodontic Clinic for follow-up care after 4 years to assess the clinical result in terms of the gap between the post-operative and residual gutta-percha. The cemented posts were divided into three groups depending on the space between the cemented post end and the remaining gutta-percha: group I revealed no gaps, group II revealed gaps between >0.1 and 1 mm, and group III revealed gaps more than 1 mm. The periapical index (PAI) was used to determine the apical condition of each tooth. Chi-square test was used for evaluating the data, and a p-value of 0.05 was considered statistically significant. A total of 28.6% post and core treated teeth were found diseased while 71.4% teeth were found normal. In group I, 90% of the teeth and in group II, 66.7% of teeth were evaluated as normal; however, in group III, 41.2% teeth were found diseased. In endodontically treated teeth restored with a post and core, a gap between the apical end of the post and the coronal section of the residual gutta-percha was associated with a greater prevalence of disease. The post and core treatment by undergraduate students achieved a clinically acceptable outcome in terms of the gap between the post end and the remaining gutta-percha.

Data science explores the use of big data to gain deeper insights and generate new knowledge and innovations which can lead to economic growth and sustainable development. However, setting up data science research comes with challenges. How we engage stakeholders is a major factor that determines success. This Commentary highlights important considerations for stakeholder engagement based on the experiences of investigators in a data science for health discovery project underway in Nigeria and South Africa. The perspectives presented will guide implementation in this relatively new but rapidly growing research domain.

Background A substantial number of persons living with HIV (PLWH) in Nigeria do not experience durable viral suppression on first-line antiretroviral therapy (ART). Understanding risk factors for first-line treatment failure informs patient monitoring practices and distribution of limited resources for second-line regimens. We determined predictors of immunologic and virologic failures in a large ART delivery program in Abuja, Nigeria. Methods A retrospective cohort study was conducted at the University of Abuja Teaching Hospital, a tertiary health care facility, using data from February 2005 to December 2014 in Abuja, Nigeria. All PLWH aged ≥ 15 years who initiated ART with at least 6-month follow-up and one CD4 measurement were included. Immunologic failure was defined as a CD4 decrease to or below pre-ART level or persistent CD4 < 100 cells per mm 3 after 6 months on ART. Virologic failure (VF) was defined as two consecutive HIV-1 RNA levels > 1000 copies/mL after at least 6 months of ART and enhanced adherence counselling. HIV drug resistance (Sanger sequences) was analyzed using the Stanford HIV database algorithm and scored for resistance to common nucleoside reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (NNRTIs). Univariate and multivariate log binomial regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CIs). Results Of 12,452 patients followed, a total of 5928 initiated ART with at least 6 months of follow-up and one CD4 measurement. The entry point for 3924 (66.2%) was through the program’s own voluntary counseling and testing (VCT) center, while 1310 (22.1%) were referred from an outside clinic/program, 332 (5.6%) in-patients, and 373 (6.3%) through other entry points including prevention of mother to child transmission (PMTCT) and transferred from other programs. The mean CD4 at enrollment in care was 268 ± 23.7 cells per mm 3 , and the mean HIV-1 RNA was 3.3 ± 1.3.log 10 copies/mL. A total of 3468 (80.5%) received nevirapine (NVP) and 2260 (19.5%) received efavirenz (EFV)—based regimens. A total of 2140 (36.1%) received tenofovir (TDF); 2662 (44.9%) zidovudine (AZT); and 1126 (19.0%) stavudine (d4T). Among those receiving TDF, 45.0% also received emtricitabine (FTC). In a multivariate model, immunologic failure was more common among PLWH with female gender as compared to male [RR (95% CI) 1.22 (1.07–1.40)] and less common among those who entered care at the program’s VCT center as compared to other entry points [0.79 (0.64–0.91)], WHO stage 3/4 as compared to 1/2 [0.19 (0.16–0.22)], or CD4 200 + cells per mm 3 as compared to lower [0.19 (0.16–0.22)]. Virologic failure was more common among PLWH who entered care at the program’s VCT center as compared to other entry points [RR (95% CI) 1.45 (1.11–1.91) and those with CD4 < 200 cells per mm 3 at entry into care as compared to higher [1.71 (1.36–2.16)]. Of 198 patient-derived samples sequenced during virologic failure, 42 (21%) were wild-type; 145 (73%) carried NNRTI drug resistance mutations; 151 (76.3%) M184I/V; 29 (14.6%) had ≥ 3 TAMs, and 37 (18.7%) had K65R, of whom all were on TDF-containing first-line regimens. Conclusions In this cohort of Nigerian PLWH followed for a period of 9 years, immunologic criteria poorly predicted virologic failure. Furthermore, a subset of samples showed that patients failing ART for extended periods of time had HIV-1 strains harboring drug resistance mutations.

This study aims to synthesise recent findings on the outcomes of common femoral endarterectomy (CFE) with profundoplasty, evaluating the efficacy, complications, and predictors of long-term success in patients undergoing this procedure. This is a descriptive retrospective study assessing the outcomes of CFE with profundoplasty. All patients with chronic limb-threatening ischaemia (CLTI) who attended and underwent CFE with profundoplasty with or without iliac intervention at Glan Clwyd Hospital (Wales, United Kingdom) were studied. We excluded the patients who had the CFE as part of bypass surgery. In a period of three years, 77 patients were included. Forty-six (59.7%) of them were male, and 31 (40.3%) of them were female. The mean age was 73.3 ± 7.8 years (standard deviation). Regarding the comorbidity, hypertension and smoking were recorded for most of the patients, while the other comorbidities were less frequent. The majority of the patients are presented with rest pain 70.1% (n = 54), while the remainder has both rest pain and tissue loss. Forty patients (51.9%) had CFE as part of the hybrid operation with iliac angioplasty; however, only 37 patients (48.1%) had CFE. The most reported complications postoperatively were groin infection, hospital-acquired pneumonia, and thrombosis, with less reporting for the rest of the complications. The limb salvage rate was 74% (n = 57); moreover, the mean primary patency rate was 10.7 + 8.4 months SD. The CFE is a feasible operation, either isolated or in conjunction with iliac angioplasty, with a satisfactory patency rate. It can be offered to the high-risk group of patients. However, they are going to need a rigorous follow-up to avoid or minimise postoperative complications.