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Drawing on the notion of channel capability, we develop a theoretical ramework for understanding the interactions between mobile and traditional online channels for products with different characteristics. Specifically, we identify two channel capabilities-access and search capabilities-that differentiate mobile and online channels, and two product characteristics that are directly related to the channel capabilities-time criticality and information intensity. Based on this framework, we generate a set of predictions on the differential effects of mobile channel introduction across different product categories. We test the predictions by applying a counterfactual analysis based on vector autoregression to a large panel data set from a leading e-market in Korea that covers a 28-month period and contains all of the transactions made through the online and mobile channels before and after the mobile channel introduction. Consistent with our theoretical predictions, our results suggest that the performance impact of the mobile channel depends on the two product characteristics and the resulting product-channel fit. We discuss implications for theory and multichannel strategy.

With the introduction of new interventions to prevent leprosy, such as post-exposure prophylaxis (PEP) given to contacts of leprosy patients, it is necessary to update our understanding of knowledge and perception of leprosy among the populations where these interventions will be introduced, in order to tailor communication optimally to the current situation. This study is a baseline study of the PEP++ project and aimed to assess the knowledge, attitudes and practices regarding leprosy in Fatehpur, India. The study used a community-based cross-sectional design with a mixed-methods approach. We assessed knowledge, attitudes, and practices with the KAP measure, and stigma with the Explanatory Model Interview Catalogue community stigma scale (EMIC-CSS) and the Social Distance Scale (SDS). In addition, semi-structured interviews and focus group discussions were conducted with all participant groups. The quantitative data were analysed using stepwise multivariate regression. The qualitative data were analysed using open, inductive coding and content analysis. A total of 446 participants were included in the study: 100 persons affected by leprosy, 111 close contacts, 185 community members and 50 health care workers. In addition, 24 in-depth interviews were conducted and 35 people were included in focus group discussions. 12.5% of the participants had adequate knowledge of leprosy, while 22% had poor knowledge. Knowledge on cause (answered correctly by 10% of the participants), mode of transmission (5%) and symptoms of leprosy (16%) was especially poor. The mean EMIC-CSS score was 15.3 (95%CI 14.6-16.0) and mean SDS score 7.2 (95%CI 6.6-7.8). Better knowledge of leprosy was associated with lower levels of social distance towards persons affected by leprosy. This study revealed poor knowledge regarding leprosy and high levels of stigma and fear and desire to keep social distance towards persons affected by leprosy. Community education that takes cultural beliefs, knowledge gaps and fears into consideration could improve knowledge, reduce misconceptions and positively influence the perception of leprosy.

Insecticide resistance in malaria vectors has created an urgent need for alternative, non-insecticidal control tools. In response, a novel window screen, the Three-dimensional (3D) Screen, was developed. Before launching a cluster-randomized controlled trial to evaluate its impact, a baseline study was conducted in 20 hamlets (clusters) from 17 villages in Muheza District, northeastern Tanzania, to assess malaria burden, vector characteristics, and risk factors for infection. Structured questionnaires collected household information; malaria prevalence was measured among 778 children aged 6 months to 14 years using malaria rapid diagnostic tests (mRDTs), and haemoglobin was assessed by HemoCue. Indoor Centers for Disease Control and Prevention (CDC) light traps (LTs) were used for mosquito collections, yielding 14,263 mosquitoes morphologically identified, including 889 Anopheles gambiae sensu lato (s.l.) and 2,013 An. funestus senso lato (s.l.); 2,508 female Anopheles were further analysed by Polymerase chain reaction (PCR). World Health Organization (WHO) cylinder bioassays assessed pyrethroid resistance in An. gambiae s.l., and genotyping targeted the knockdown resistance (kdr)-East (L1014S) mutation. Malaria prevalence was 40.2%, and anaemia affected 55.2% of children. An. funestus s.l. (70.2%) and An. gambiae s.l. (29.8%) comprised the vector population. Mean daily entomological inoculation rates (EIRs) were 0.039 and 0.037 infectious bites per person per night, corresponding to annual EIRs of approximately 14.2 for An. funestus s.l., 13.5 for An. gambiae s.l., and 27.7 combined. Pyrethroid resistance was high, with 24-hour mortality of 56.5% to permethrin and 52.8% to deltamethrin; the kdr-East (L1014S) allele frequency in An. gambiae s.s. was 0.45. Multivariate analysis showed that children aged ≥ 5 years had approximately threefold higher odds of Plasmodium infection than those < 5 years (aOR = 3.03, 95% CI: 2.09–4.40), while sleeping under a bed net was protective (aOR = 0.36, 95% CI: 0.18–0.70). Cluster-level variance accounted for 19.5% of infection risk, highlighting community-level factors. Persistent transmission, high anaemia prevalence, and widespread insecticide resistance underscore the limitations of current measures and the need for integrated interventions, including novel non-insecticidal tools such as the 3D-Screen.

Purpose This study aimed to analyze baseline predictors of functional outcomes six weeks and at one year follow-up in patients older than 60 years with complex regional pain syndrome type 1 (CRPS I) after distal radius fracture (DRF). Methods A total of 120 patients with CRPS I after DRF were prospectively recruited. Presumptive relevant factors were collected and analyzed as potential baseline predictors. Additionally, functional outcomes were assessed at the beginning of physiotherapy treatment, at six weeks after finishing physiotherapy treatment, and at one year follow-up. Patient-Rated Wrist Evaluation; Disabilities of the Arm, Shoulder, and Hand (DASH) questionnaire; Jamar dynamometer; and visual analog scale (VAS) were assessed. Results All participants completed the study. At 6 weeks, the main results showed an association of lower values of grip strength with female sex ( p = 0.010), intra-articular DRFs ( p = 0.030), longer immobilization time ( p = 0.040), lower levels of physical activity ( p < 0.001), higher levels of kinesiophobia ( p = 0.010), and anxiety ( p = 0.020). At 1-year follow-up, the results showed an association of lower values of DASH with higher BMI ( p < 0.001) and longer immobilization time ( p < 0.001); and higher values of VAS showed an association with older age ( p = 0.010), higher BMI ( p = 0.010), and lower levels of physical activity ( p = 0.040). Conclusion At six weeks, factors such as BMI, immobilization time, physical activity, and kinesiophobia are associated with lower functional outcomes. Additionally, at one year follow-up, BMI, immobilization time, and physical activity continue to be associated with lower functional outcomes in patients with CRPS I after DRF treated conservatively.

Immune checkpoint inhibitors (ICI) are a novel medication for non-small cell lung cancer (NSCLC). Recent reports indicated that baseline tumor size (BTS) relates to the efficacy of ICI therapy for melanoma, but no study exists for NSCLC. This study aimed to evaluate the utility of BTS for ICI therapy. Data from 58 patients diagnosed with NSCLC who underwent ICI monotherapy, were retrospectively analyzed. Patients were divided into two groups according to BTS (below 101 mm, above 101 mm). The primary endpoint was progression-free survival (PFS) and the secondary endpoint was overall survival (OS). PFS of patients with a large BTS was significantly shorter than that of those with a small BTS (median; 2.07 [95% confidence interval [CI]=0.99-6.77] months versus 6.39 [95%CI=4.17-11.50] months) (p=0.044). OS of patients with large BTS was also significantly shorter (p<0.01). BTS is a predictive and prognostic negative factor of ICI therapy for NSCLC.

Abstract The aim of the current study is to apply multivariate singular spectrum analysis (M-SSA) techniques and investigate both shallow and intermediate-depth earthquake characteristics in eastern Nepal and the southern Tibetan Himalaya. Space–time-depth-magnitude (STDM) domain time-series were computed for a time window of 776 events, using a complete catalog (2005–2020) provided by the European-Mediterranean Seismological Center. Several criteria and tests, such as the quantile–quantile plot, Hankel matrix, and principal and reconstruction components analysis of STDM time-series were introduced to characterize the causality and predictability of seismic changes. It was evident from the quantile–quantile plot those events (Mw) do not approximate a linear trend but present a nonlinear trend, which is possibly due to the unusual seismically generated strain that cannot be accurately unstable compared to large earthquakes. Principal component analysis of the Hankel matrix strongly influences the ability of M-SSA to extract the measured and noise errors of an STDM time-series. Based on a reconstruction component analysis, the separability of the varying correlation coefficient between measured and predicted STDM time-series was evaluated and reconstructed in three groups: trend, oscillating, and noise group components. In conclusion, supporting the current research, it can be claimed that the results serve as a baseline study of seismicity using the M-SSA approach; by taking the example of eastern Nepal and the southern Tibetan Himalaya, users will be able to utilize M-SSA at the global level.

Although ustekinumab (UST) has been recommended by guidelines as a parallel first-line biologic agent for Crohn's disease (CD), its efficacy varies among individuals. This study aimed to identify baseline clinical features and laboratory indicators that can predict clinical remission with UST to assist clinical decision-making. This retrospective study collected data from patients with CD who received UST induction and maintenance therapy across multiple centers. The primary endpoint was the rate of clinical remission at week 48. Independent predictors of clinical remission were identified by multivariate logistic regression analysis. Receiver operating characteristic (ROC) curves and the Youden index were used to determine optimal cutoff values. Among the 157 included patients, clinical and endoscopic remission rates were 76.4% (120/157) and 51.6% (81/157), respectively. Multivariate analysis showed that baseline neutrophil count and baseline platelet-lymphocyte ratio (PLR) were independent predictors of clinical remission at week 48 with UST treatment. Area under the ROC curve values for baseline neutrophil count, baseline PLR, and their combination were 0.633, 0.709, and 0.769, respectively. Optimal cutoff values for baseline neutrophil count and baseline PLR were ≤4.135×10 /L and <237.912, respectively. Baseline neutrophil count and baseline PLR together constitute a simple and effective predictive model. This model may help identify patients who are more responsive to UST before treatment, offering a practical tool for individualized and precise treatment of CD.

This study is on the outskirts of the rapidly growing city of Jaipur, located in the semiarid region of India and gateway to the ‘Great Indian Thar’ desert, and focused on potentially toxic elements (PTE) pollution in the farmlands around the city. Concentrations of PTE, along with associated soil parameters such as pH, available nitrogen, organic carbon, phosphorus, and potassium, were estimated in agricultural soil samples near an industrial region on the outskirts of the capital city of the largest state of India. The PTE concentrations in the soil were in the following order: Mn > Pb > Ni > Cr > Cu > Cd. Soil pollution indices, such as the geochemical accumulation index (Igeo), contamination factor (CF), and ecological risk index (ERI), indicated that the soil was moderately to highly polluted. The result of BCR extraction techniques showed Cd is found mainly in the exchangeable and residual fractions, Pb, Mn were found in the reducible as well as residual fractions, while other PTE were mostly bound to residual fraction. All other PTEs are primarily found in the residual fraction, tightly linked with the silicate lattice of soil minerals. Multivariate analysis and the Pearson correlation matrix indicate a common source apportionment for Pb and Cd. Cd, and Pb concentrations in agricultural soil indicate ecological harm that warrants immediate attention and policy-level intervention.

A total of 21 surface sediment samples collected from Arasalar River are subjected to sediment texture (sand-silt-clay ratio), trace elements, organic matter, and CaCO 3 studies to understand the accumulation dynamics of sediments. To assess the impact of metal pollution in estuarine sediments, the essential parameters should be done by checking the sediment characteristics, spatial distribution of heavy metal sources, sediment dynamics, and geochemical analysis. To evaluate the contamination level of metal pollution, a basic standard reference is required to decipher the values ranging from natural to anthropogenic contribution. From this research analysis, it is observed that the study area predominantly comprises silty sand and sand silty nature. The calcium carbonate content in the sediment is found to be proportional to the presence of shell fragments, whereas the organic matter (OM) is derived from riverine and coastal input which acts as a primary source. The obtained results confessed the average contents (mg/g) for the following selected eight elements in the order of Fe (35249–49068) > Mn (286–519) > Ni (107–279) > Cu (78.30–155.70) > Cr (50–99) > Zn (38.70–91.90) > Pb (39.90–62.40), and Co (12.6–29.1) by using an atomic absorption spectrophotometer (AAS) are utilized for this analysis. Multivariate analysis of heavy metals affirms geogenic sources (weathering of parent rocks) for Fe, Mn, Cr, Co, and Zn, whereas Cu, Ni, and Pb originated from anthropogenic activities (urban and industrial activities). The pollution load index, sediment pollution index, I geo index, and PERI are categorized as under polluted, low to moderate polluted, and low potential environmental risk variety. Constant inspection and guidance are needed to prevent effluences from various agriculture and industrial activities in the nearby regions. The findings from this research may support and help the government to follow the suitable remediation on the better management of river and coastal areas.

Intense land use, driven by mining and agriculture, promotes the dispersal of elements, including potentially toxic ones (PTEs). This dispersal significantly enhances element concentrations in soils, sediments, and water bodies, thereby altering the natural background values of the environment. The objective of this paper is to employ geochemical mapping alongside multivariate statistical methods to establish the baseline values for the Mining Zinc District situated at the boundary of the São Francisco Craton and Brasília Belt. This will facilitate the assessment of spatial variability and determination of reference values for element concentrations in sediment samples, enabling the differentiation between natural and anthropogenic sources of potentially toxic elements. A geochemical database of 1853 sediment samples were assembled from the São Francisco and Paranaíba watersheds for subsequent ICP-OES and ICP-MS analysis. The baseline values were assessed through 3 distinct methods, while the Factor Analysis was employed as a multivariate statistical technique. The findings reveal that the baseline concentrations of Ni (415 mg.kg −1 ), Cr (137 mg.kg −1 ), and Co (106 mg.kg −1 ) were higher than the Investigation Values of CONAMA Resolution n°454/2012. The factor analysis found 6 main factors that explain 75.1% of the total system variance. It also found 8 major geochemical links between these factors: (1) Al, Cs, Ga, Sn, and V; (2) Co, Mg, Ni, and Zn; (3) Cr, Ni, and V; (4) Cs, K, and Rb; (5) As, and Fe; (6) Cd, Pb, and Zn; (7) LREE, Th, and U; and (8) Ba, P, and Sr.